Rachael Marie B. Rosario1-2, Ana Patricia A. Alcasabas1-3, Corazon A. Ngelangel1-2, Adriano V. Laudico1,4, Rica M. Lumague4, Edmund A. Orlina4, Cynthia A. Mapua1,4, Maricar R. Sabeniano1, Vianna R. Yunque4, Rauell John Santos5, Rey Arturo Fernandez5, Jan Aure Llevado6, Alyanna Riel Panlilio6
1Philippine Cancer Society Manila Cancer Registry, 2 University of the Philippines-College of Medicine,3 Philippine Society of Pediatric Oncology, 4DOH-Rizal Cancer Registry, 5World Health Organization-WPRO, 6DOH-Cancer Control Division
Corresponding author: Corazon A. Ngelangel; philippinecancer.org@gmail.com
ABSTRACT
Objective: This retrospective cohort study aims to determine the population-based five-year survival rate of patients aged 0-19 years diagnosed with cancer in the era before the National Integrated Cancer Control Act (NICCA) was signed into law. The study focuses on lymphoid leukemia, Hodgkin’s lymphoma, Burkitt’s lymphoma, retinoblastoma, nephroblastoma, and osteosarcoma.
Methods: The study utilizes data from two primary sources: the Philippine Cancer Society – Manila Cancer Registry (PCS – MCR) and the Department of Health – Rizal Cancer Registry (DOH-RCR). The cohort includes patients diagnosed between 2006 and 2017, providing a comprehensive dataset for analysis of survival rates in the pre-NICCA period.
Results: The survival rates for the above specific pediatric cancer types in the Philippines were low. Possible barriers include financial constraints, difficulties accessing diagnostic and treatment services, and awareness issues. The Acute Lymphoid Leukemia (ALL) DOH- Childhood Cancer Medicine Access Program (CCMAP) and PhilHealth Z package improved ALL survival rates. The significance of targeted healthcare programs and areas for improvement, such as enhanced access to comprehensive care, is highlighted. The DOH-CCMAP expansion to include other cancers and upgrading children’s services in DOH-designated cancer centers across the country, mandated by the National Integrated Cancer Control Act (NICCA), are welcome to control pediatric cancer. In 2030, perhaps cancer survival rates would significantly improve.
Conclusion: The study reveals low survival rates for specific pediatric cancers in the Philippines, highlighting the need for improved access to comprehensive care and targeted healthcare programs. Implementing the National Integrated Cancer Control Act, expanding the DOH- CCMAP, and upgrading children’s services in cancer centers nationwide are promising steps toward improving pediatric cancer outcomes in the country.
Keywords: Childhood cancer survival, population-based cancer registry, PCS-MCR, DOH-RCR
INTRODUCTION
The global burden of pediatric cancer is growing, with an estimated 400,000 children developing cancer each year.1 Disparities in survival rates between high-income countries (HICs) and low-
middle-income countries (LMICs) are significant, with average global survival rates of 37%, ranging from 90% in HICs to less than 30% in LMICs.2-4
In the Philippines, about 3% of cancers occur in children aged <14 years, and cancer ranks third leading cause of morbidity and mortality.5 Although developed countries have high survival rates of 80-90%, <30% of children survive in developing countries.2-3
Annually, approximately 4700 Filipino children aged 0-19 years are expected to be diagnosed with cancer, and 1700 Filipino childhood deaths will be due to cancer.6 Unfortunately, although multidisciplinary management is available and could potentially cure 80% of such cases, only about 10-20% attain long-term survival.5 The obstacles to early detection and effective management of childhood cancer in the Philippines include the lack of prompt recognition of subtle signs and symptoms, patients and parents delaying medical consultations, lack of cancer treatment facilities in the locality, costly treatment, abandonment of treatment, and advanced stages on initial medical consultation.5 Out of the 20-30% of children diagnosed early, a significant percenage cannot continue follow-up visits or hospitalization.5 Locally, inequity exists between high-income and low-income families’ capacity to access affordable cancer care.
Stakeholders must implement measures that address the issue of inequity of cancer care in the Philippines by providing support, advocacy, and resources for preventing, detecting, and treating childhood cancer.
In 2018, WHO launched the Global Initiative for Cancer Control (GICC) to address the increasing burden of childhood cancer and reduce survival rate disparities between HICs and LMICs.6 The GICC aims to raise the global survival rate of children with cancer to at least 60% by 2030, saving an additional one million lives. This goal is supported by the WHO CureAll framework, which outlines programs and priority interventions under four pillars: Centers of excellence and care networks with a sufficient and competent workforce to increase capacity to deliver quality patient- centered services, Universal health coverage by integrating childhood cancer as part of the full range of essential quality-assured services and included in benefit packages, Regimens and roadmaps for diagnosis and treatment that are context appropriate and facilitate delivery of quality services through evidence-based utilization of essential health products, and Evaluation and monitoring with robust information systems.7-8
Before the GICC, several cancer control programs had already been implemented in the Philippines. These efforts included the ALL DOH-CCMAP and the PhilHealth Z package, which started in 2012.9 The DOH-ALL CCMAP provides subsidized drugs to treat children with ALL. The PhilHealth ALL-Z package offers additional support for cancer patients, covering the cost of diagnostic and other treatment services.9 Before 2022, there was no PhilHealth Z-package nor DOH CCMAP for other childhood cancer types. Some hospitals (e.g., Philippine General Hospital, Philippine Children Medical Center, and National Children Medical Center) have children cancer- focused services with experts in pediatric oncology.
The NICCA was signed into law on 14 February 2019.10 This Law establishes a comprehensive and integrated approach to cancer control in the Philippines and mandates the development and implementation of a national cancer control program encompassing health promotion, prevention, early detection, diagnosis, treatment, palliative care as well as capacity building, research, and financing mechanisms to improve access to care and support services for cancer patients and their families.
Strengthening local cancer registries towards a national cancer registry measures the country’s efforts for pediatric cancer control. Section 28 of NICCA explicitly states the need to establish a national cancer registry, which will be a population-based cancer registry (PBCR) that collects
data per geographical region to provide a framework for assessing and controlling the impact of cancer on the community.
Both the GICC and NICCA encourage PBCRs. Unlike hospital-based cancer registry (HBCR), PBCR provides a more comprehensive picture of the cancer burden within a community and enables the monitoring and Evaluation of cancer control activities at the population level. Hospitals are mandated to have medical records (MR), eventually electronic MR, from which they can cull out their own HBCR.
The Philippines has two PBCRs, the Philippine Cancer Society–Manila Cancer Registry (PCS– MCR) and the Department of Health–Rizal Cancer Registry (DOH–RCR), which gather data on cancer, including on children from the Metro Manila 16 cities and 14 municipalities.11-12 Both registries are recognized by the WHO-International Agency for Research on Cancer (IARC)13 and produced incidence data published in the International Incidence of Childhood Cancer Volumes 2 and 3. Population-based cancer survival data reflects the impact of national cancer control programs and policies.
We determined the population-based five-year survival rate of pediatric patients diagnosed with select specific cancers from the PCS-MCR and DOH-RCR catchment areas covering the years 2006-2017, serving as a baseline prior to the implementation of NICCA.
METHODS
This project was conducted with the DOH Cancer Control Division and WHO-WPRO. This retrospective cohort included children registered in the PCS-MCR and DOH-RCR, aged 0-19 years, who were diagnosed with primary cancer between 1 January 2006 and 31 December 2017. The children were with histopathological or cytological confirmed diagnosis of cancer. Excluded were those registered based on death certificates or autopsy reports only or with incomplete or missing birth dates, diagnosis, or last known vital status, incoherent data sequences, and non- malignant tumors.
Data extracted from preexisting databases PCS-MCR and DOH-RCR included date of diagnosis, age at diagnosis, sex, cancer type, basis of diagnosis, extent of disease, initial treatment, date of death or date of last contact, vital status, cause of death, and place of death. For cases without death records in the PBCRs, death status was ascertained from the Local Civil Registries.
Descriptive statistics such as mean and standard deviations for quantitative data and frequencies and proportions for categorical data were used to summarize the demographic and clinical characteristics of the study population. Researchers used survival analysis to study the WHO GICC index childhood cancers (lymphoid Leukemia, Hodgkin’s lymphoma, Burkitt’s lymphoma, retinoblastoma, nephroblastoma) and osteosarcoma, a common cancer among adolescent Filipino children. Researchers used Kaplan-Meier survival analysis to estimate the overall 5-year survival rates and median survival times for different groups defined by cancer type, age group, sex, stage, and treatment. Particularly for Leukemia, they compared survival rates between the pre-and post- implementation periods of the ALL DOH-CCMAP and PhilHealth Z packages. Log-rank tests were used to assess the differences in survival between these groups statistically.
RESULTS
Data on a total of 2685 cases were secured from PCS-MCR and DOH-RCR with diagnoses of lymphoid Leukemia, Hodgkin’s lymphoma, Burkitt’s lymphoma, retinoblastoma,
nephroblastoma, and osteosarcoma (Table 1). Of these, 2256 (84%) cases were included in the analysis (Table 2), representing 58% of all children with cancer within the study period. The total number of cancer cases in the DOH-RCR and PCS-MCR 2006-2017 was 100,567 (96,654 adults and 3,913 children).
Basis of diagnosis
Cancer
Total
registered
DCO
Non-microscopic
Microscopic
n
%
N
%
n
%
Lymphoid Leukemia
1569
16
1.0
5
0.3
1548
98.7
Hodgkin’s lymphoma
194
0
0.0
1
0.5
193
99.5
Burkitt’s lymphoma
76
0
0.0
0
0.0
76
100.0
Retinoblastoma
265
6
2.3
13
4.9
246
92.8
Nephroblastoma
169
1
0.6
9
5.3
159
94.1
Osteosarcoma
412
2
0.5
5
1.2
405
98.3
TABLE 1 Number and proportion of microscopically verified and death certificate-only cases by childhood cancers, RCR and MCR, 2006-2017.
TABLE 2 Number and proportion of included and excluded cases by childhood cancers, RCR and MCR, 2006-2017.
Excluded cases
Total registered
No follow-up information
Duplicate cases, secondary
primary
Included cases
Cancer
DCO
N
%
N
%
n
%
n
%
Lymphoid Leukemia
1569
49
3.1
75
4.8
18
1.1
1427
90.9
Hodgkin’s lymphoma
194
1
0.5
13
6.7
6
3.1
174
89.7
Burkitt’s lymphoma
76
0
0.0
0
0.0
0
0.0
76
100.0
Retinoblastoma
265
5
1.9
31
11.7
5
1.9
224
84.5
Nephroblastoma
169
7
4.1
12
7.1
2
1.2
148
87.6
Osteosarcoma
412
4
1.0
20
4.9
4
1.0
384
93.2
Lymphoid Leukemia
The majority of children with lymphoid Leukemia were diagnosed in government hospitals (79.4%), belonged to the age groups of 1-4 (41.41%) and 5-9 years (31.6%), and were male
(60.2%) (Table 3).
TABLE 3 Characteristics of childhood lymphoid leukemia, RCR and MCR, 2006-2017.
Characteristics
Lymphoid Leukemia
(N=1427)
n
%
Registry
PCS-MCR
736
51.6%
DOH-RCR
691
48.4%
Place of diagnosis
Government hospital
1133
79.4%
Private hospital
260
18.2%
Private clinic
21
1.5%
Home
1
0.1%
Other hospital
12
0.8%
Year of diagnosis
Before ALL DOH-CCMAP and PhilHealth Z packages
754
52.8%
After ALL DOH-CCMAP and PhilHealth Z packages
673
47.2%
Age group
< 1
37
2.6%
1 – 4
587
41.1%
5 – 9
451
31.6%
10 – 14
215
15.1%
15 – 19
137
9.6%
Sex
Male
859
60.2%
Female
568
39.8%
Extent of disease
Localized
0
0.0%
Regional
2
0.1%
Distant metastasis
740
51.9%
Unknown
685
48.0%
Initial treatment
Without treatment
2
0.1%
With treatment
328
23.0%
Unknown
1097
76.9%
Status at five years
Alive
778
54.5%
Dead
649
45.5%
The cumulative 5-year survival rate for all lymphoid leukemia cases was 19.9%, with a median survival time of 11.6 months (Table 4, Figure 1).
TABLE 4 Childhood lymphoid leukemia survival, RCR, and MCR, 2006-2017.
No. of cases
5-year observed survival (%)
Median survival time
Log-rank test
p-value
Total
Events
Censored
Months
95% CI
All cases
1427
649
778 (54.5%)
19.9%
11.6
9.8-13.4
—
Registry
0.668
PCS-MCR
736
373
363 (49.3%)
16.7%
10.1
8.8-11.4
DOH-RCR
691
276
415 (60.1%)
24.7%
15.5
10.1-20.8
Age group
<0.001
< 1
37
14
23 (62.2%)
≤18.0%
13.5
2.3-24.8
1 – 4
587
264
323 (55.0%)
22.8%
13.2
9.5-16.9
5 – 9
451
157
294 (65.2%)
31.9%
24.0
15.5-32.5
10 – 14
215
124
91 (42.3%)
6.2%
8.7
7.6- 9.8
15 – 19
137
90
47 (34.3%)
0.0%
5.4
3.5- 7.4
Sex
0.809
Male
859
400
459 (53.4%)
21.7%
11.1
9.3-12.9
Female
568
249
319 (56.2%)
16.3%
13.5
9.9-17.2
Extent of disease
0.003
Localized
0
—
—
—
—
—
Regional
2
0
2 (100.0%)
≤100.0%
—
—
Distant metastasis
740
344
396 (53.5%)
20.3%
9.4
6.9-11.8
Unknown
685
305
380 (55.5%)
19.7%
13.8
10.6-16.9
Initial treatment
<0.001
Without treatment
2
2
0 (100.0%)
0.0%
0.2
—
With treatment
328
82
246 (75.0%)
42.1%
40.4
26.4-54.3
Unknown
1097
649
539 (48.5%)
12.7%
7.9
7.0- 8.8
Period of diagnosis
<0.001
Before ALL DOH-CCMAP
and PhilHealth Z packages
754
397
357 (47.3%)
17.5%
8.6
7.4- 9.8
After ALL DOH-CCMAP and PhilHealth Z packages
673
252
428 (62.6%)
22.0%
18.7
14.5-22.9
FIGURE 1 Childhood lymphoid leukemia overall survival, RCR, and MCR, 2006-2017.
Survival by age group was better in the 5-9 and 1-4 age groups. Worse survival was in the 10-14 and 15-19 years age groups (Figure 2).
FIGURE 2 Childhood lymphoid leukemia survival by age group, RCR and MCR, 2006-2017.
FIGURE 3 Childhood lymphoid leukemia survival by sex, RCR and MCR, 2006-2017.
Survival by extent of disease was significantly different but almost similar as survival time lengthened (Figure 4). Better survival was in those with treatment (Figure 5). However, many patients had an unknown extent of disease and an unknown initial treatment; 2 cases were without treatment, and 0 localized and two regional diseases.
FIGURE 4 Childhood lymphoid leukemia survival by extent of disease, RCR and MCR, 2006-2017.
FIGURE 5 Childhood lymphoid leukemia survival by initial treatment, RCR, and MCR,2006-2017.
FIGURE 6 Childhood lymphoid leukemia survival by the registry, RCR, and MCR, 2006-2017.
Better survival was in cases diagnosed after the implementation of ALL PhilHealth Z packages and DOH-CCMAP (Figure 7).
FIGURE 7 Childhood lymphoid leukemia survival by incidence period, RCR and MCR, 2006-2017.
Hodgkin’s Lymphoma
In children with Hodgkin’s Lymphoma, the majority were diagnosed in government hospitals (54.6%), belonged to the 15-19 years age group (67.2%), and were male (57.5%) (Table 5).
TABLE 5 Characteristics of childhood Hodgkin lymphoma, RCR and MCR, 2006-2017.
Characteristics
Hodgkin lymphoma (N=174)
n
%
Registry
PCS-MCR
95
54.6%
DOH-RCR
79
45.4%
Place of diagnosis
Government hospital
95
54.6%
Private hospital
78
44.8%
Other hospital
1
0.6%
Age group
< 1
0
0.0%
1 – 4
3
1.7%
5 – 9
15
8.6%
10 – 14
39
22.4%
15 – 19
117
67.2%
Sex
Male
100
57.5%
Female
74
42.5%
Extent of disease
Localized
5
2.9%
Regional
1
0.6%
Distant metastasis
12
6.9%
Unknown
156
89.7%
Treatment
Treatment given
81
46.6%
Unknown
93
53.4%
Status
Alive
137
78.7%
Dead
37
21.3%
The cumulative 5-year survival rate of all Hodgkin’s lymphoma cases was 24.0%, with a median survival time of 35.1 months (Table 6, Figure 8).
TABLE 6. Childhood Hodgkin lymphoma survival, RCR and MCR, 2006-2017.
No. of cases
5-year observed survival (%)
Median survival time
Log-rank test
p-value
Total
Events
Censored
Months
95% CI
All cases
174
37
137 (78.7%)
24.0%
35.1
21.7-48.5
—
Registry
0.740
PCS-MCR
95
24
71 (74.7%)
29.8%
28.2
2.0-54.4
DOH-RCR
79
13
66 (83.5%)
0.0%
35.1
20.4-49.8
Age group
0.002
< 1
0
—
—
—
—
—
1 – 4
3
0
3 (100.0%)
≤100.0%
—
—
5 – 9
15
8
7 (46.7%)
0.0%
8.4
7.9- 8.9
10 – 14
39
7
32 (82.1%)
0.0%
41.6
8.4-74.8
15 – 19
117
22
95 (81.2%)
34.7%
43.5
30.1-56.9
Sex
0.637
Male
100
22
78 (78.0%)
20.3%
35.1
12.4-57.9
Female
74
15
59 (79.7%)
36.4%
40.3
22.1-58.4
Extent of disease
0.135
Localized
5
0
5 (100.0%)
≤100.0%
—
—
Regional
1
0
1 (100.0%)
≤100.0%
—
—
Distant metastasis
12
6
6 (50.0%)
0.0%
12.0
0.0-32.5
Unknown
156
31
125 (80.1%)
26.1%
35.1
22.0-48.3
Initial treatment
<0.001
Without treatment
0
—
—
—
—
—
With treatment
81
10
71 (87.7%)
50.2%
—
—
Unknown
93
27
66 (71.0%)
9.0%
20.7
12.5-28.8
FIGURE 8 Childhood Hodgkin lymphoma overall survival, RCR and MCR, 2006-2017.
Survival was significantly better in the age groups of 15-19 and 10-14 and worse in the age group of 5-9 years (Figure 9) and in those with treatment (Figure 12). Note, however, that many patients had an unknown extent of disease and an unknown initial treatment; 5 had localized disease.
FIGURE 9 Childhood Hodgkin’s lymphoma survival by age group, RCR and MCR, 2006-2017.
FIGURE 10 Childhood Hodgkin’s lymphoma survival by sex, RCR and MCR, 2006-2017.
FIGURE 11 Childhood Hodgkin’s lymphoma survival by extent of disease, RCR and MCR, 2006-2017.
FIGURE 12 Childhood Hodgkin lymphoma survival by initial treatment, RCR and MCR, 2006-2017.
FIGURE 13 Childhood Hodgkin’s lymphoma survival by registry, RCR and MCR, 2006- 2017.
Burkitt’s Lymphoma
In children with Burkitt’s Lymphoma, the majority were diagnosed in government hospitals (88.2%), belonged to the 1-4 (40.8%) and 5-9 years (31.6%) age groups, were male (68.4%), and
had distant metastasis (56.6%) (Table 7).
TABLE 7 Characteristics of childhood Burkitt’s lymphoma, RCR, and MCR, 2006-2017.
Characteristics
Burkitt’s lymphoma (N=76)
N
%
Registry
PCS-MCR
18
23.7%
DOH-RCR
58
76.3%
Place of diagnosis
Government hospital
67
88.2%
Private hospital
9
11.8%
Age group
< 1
2
2.6%
1 – 4
31
40.8%
5 – 9
24
31.6%
10 – 14
13
17.1%
15 – 19
6
7.9%
Sex
Male
52
68.4%
Female
24
31.6%
Extent of disease
Localized
0
0.0%
Regional
1
1.3%
Distant metastasis
43
56.6%
Unknown
32
42.1%
Treatment
Treatment given
13
17.1%
Unknown
63
82.9%
Status
Alive
56
73.7%
Dead
20
26.3%
The cumulative 5-year survival rate of all cases of Burkitt’s Lymphoma was 16.7%, with a median survival time of 37.4 months (Table 8, Figure 14).
TABLE 8 Childhood Burkitt’s lymphoma survival, RCR and MCR, 2006-2017.
No. of cases
5-year observed survival (%)
Median survival time
Log-rank test
p-value
Total
Events
Censored
Months
95% CI
All cases
76
20
56 (73.7%)
16.7%
37.4
14.9-59.9
—
Registry
0.741
PCS-MCR
18
9
9 (50.0%)
16.1%
37.4
8.4-66.4
DOH-RCR
58
11
47 (81.0%)
≤39.1%
33.6
13.9-53.3
Age group
0.297
< 1
2
0
2 (100.0%)
≤100.0%
—
—
1 – 4
31
10
21 (67.7%)
0.0%
33.6
0.0-72.8
5 – 9
24
3
21 (87.5%)
≤70.5%
—
—
10 – 14
13
5
8 (61.5%)
23.1%
10.8
0.0-22.4
15 – 19
6
2
4 (66.7%)
0.0%
0.9
—
Sex
0.958
Male
52
13
39 (75.0%)
30.3%
37.4
14.1-60.6
Female
24
7
17 (70.8%)
0.0%
33.6
5.0-62.2
Extent of disease
0.614
Localized
0
—
—
—
—
—
Regional
1
0
1 (100.0%)
≤100.0%
—
—
Distant metastasis
43
7
36 (83.7%)
≤45.0%
33.6
—
Unknown
32
13
19 (59.4%)
14.1%
37.4
0.0-81.9
Initial treatment
0.626
Without treatment
0
—
—
—
—
—
With treatment
13
3
10 (76.9%)
≤40.1%
33.6
0.0-74.4
Unknown
63
17
46 (73.0%)
15.3%
37.4
20.5-54.3
FIGURE 14 Childhood Burkitt’s lymphoma overall survival, RCR and MCR, 2006-2017.
Survival was not significantly different by age group, sex, the extent of disease, initial treatment, locality, or period of diagnosis (Figures 15-21), as may be due to the relatively small number of
cases. Note that many patients had an unknown extent of disease and unknown initial treatment; no one had localized disease, and only 1 had regional disease.
FIGURE 15 Childhood Burkitt’s lymphoma survival by age group, RCR and MCR, 2006-2017.
FIGURE 16 Childhood Burkitt’s lymphoma survival by sex, RCR and MCR, 2006-2017.
FIGURE 17 Childhood Burkitt’s lymphoma survival by extent of disease, RCR and MCR, 2006-2017.
FIGURE 18 Childhood Burkitt’s lymphoma survival by initial treatment, RCR and MCR, 2006-2017.
FIGURE 19 Childhood Burkitt’s lymphoma survival by the registry, RCR, and MCR, 2006-2017.
Retinoblastoma
In children with retinoblastoma, the majority were diagnosed in government hospitals (76.8%) and belonged to the 1-4 years age group (77.2%) (Table 9).
TABLE 9 Characteristics of childhood retinoblastoma, RCR and MCR, 2006-2017.
Characteristics
Retinoblastoma
(N=224)
N
%
Registry
PCS-MCR
110
49.1%
DOH-RCR
114
50.9%
Place of diagnosis
Government hospital
172
76.8%
Private hospital
37
16.5%
Private clinic
10
4.5%
Home
4
1.8%
Other hospital
1
0.4%
Age group
< 1
31
13.8%
1 – 4
173
77.2%
5 – 9
17
7.6%
10 – 14
3
1.3%
15 – 19
0
0.0%
Sex
Male
120
53.6%
Female
104
46.4%
Extent of disease
Localized
4
1.8%
Regional
14
6.3%
Distant metastasis
19
8.5%
Unknown
187
83.5%
Treatment
Treatment given
50
22.3%
Unknown
174
77.7%
Status at five years
Alive
161
71.9%
Dead
63
28.1%
The cumulative 5-year survival rate of all retinoblastoma cases was 31.6%, with a median survival time of 11.1 months (Table 10, Figure 20).
TABLE 10 Childhood retinoblastoma survival, RCR and MCR, 2006-2017.
No. of cases
5-year observed survival
(%)
Median survival time
Log- rank test
p-value
Total
Events
Censored
Months
95% CI
All cases
224
63
161 (71.9%)
31.6%
11.1
6.8-15.4
—
Registry
0.136
PCS-MCR
110
35
75 (68.2%)
≤21.4%
8.7
6.5-10.8
DOH-RCR
114
28
90 (75.4%)
39.5%
20.7
13.7-27.8
Age group
0.010
< 1
31
1
30 (96.8%)
80.0%
—
—
1 – 4
173
56
121 (67.6%)
24.5%
10.1
8.1-12.2
5 – 9
17
5
12 (70.6%)
≤40.1%
11.1
7.0-15.2
10 – 14
3
1
2 (66.7%)
≤50.0%
5.9
—
15 – 19
0
—
—
—
—
—
Sex
0.355
Male
120
30
90 (75.0%)
≤43.3%
15.2
10.0-20.4
Female
104
33
71 (68.3%)
22.8%
10.1
7.9-12.3
Extent of disease
<0.001
Localized
4
1
3 (75.0%)
≤75.0%
—
—
Regional
14
5
9 (64.3%)
≤20.0%
15.5
5.5-25.5
Distant metastasis
19
16
3 (15.8%)
0.0%
4.5
0.7- 8.4
Unknown
187
41
150 (78.1%)
41.9%
15.2
5.2-25.2
Initial treatment
0.040
Without treatment
0
—
—
—
—
—
With treatment
50
15
35 (70.0%)
44.5%
21.1
12.6-29.6
Unknown
174
48
126 (72.4%)
≤24.6%
8.7
6.8-10.7
FIGURE 20 Childhood retinoblastoma overall survival, RCR and MCR, 2006-2017.
Survival was significantly different by age group (p = 0.010), extent of disease (p<0.001), and treatment (p = 0.040) (Figures 21, 23, 24). Note, however, that there were many patients with unknown extent of disease and unknown initial treatment; no one was without treatment, and four had localized disease.
FIGURE 21 Childhood retinoblastoma survival by age group, RCR and MCR, 2006-2017.
FIGURE 22 Childhood retinoblastoma survival by sex, RCR and MCR, 2006-2017.
FIGURE 23 Childhood retinoblastoma survival by extent of disease, RCR and MCR, 2006-2017.
FIGURE 24 Childhood retinoblastoma survival by initial treatment, RCR and MCR, 2006-2017.
FIGURE 25 Childhood retinoblastoma survival by the registry, RCR, and MCR, 2006-2017.
Nephroblastoma
In children with nephroblastoma, the majority were diagnosed in government hospitals (81.8%) and belonged to the 1-4 years age group (61.5%) (Table 11).
Table 11 Characteristics of childhood nephroblastoma, RCR and MCR, 2006-2017.
Characteristics
Nephroblastoma (N=148)
n
%
Registry
PCS-MCR
69
46.6%
DOH-RCR
79
53.4%
Place of diagnosis
Government hospital
121
81.8%
Private hospital
19
12.8%
Private clinic
7
4.7%
Other hospital
1
0.7%
Age group
< 1
15
10.1%
1 – 4
91
61.5%
5 – 9
26
17.6%
10 – 14
12
8.1%
15 – 19
4
2.7%
Sex
Male
82
55.4%
Female
66
44.6%
Extent of disease
Localized
9
6.1%
Regional
5
3.4%
Distant metastasis
25
16.9%
Unknown
109
73.6%
Treatment
None
0
0.0%
Treatment given
58
39.2%
Unknown
90
60.8%
Status
Alive
84
56.8%
Dead
64
43.2%
All nephroblastoma cases’ cumulative 5-year survival rate was 12.5%, with a median survival time of 7.8 months (Table 12, Figure 26).
TABLE 12 Childhood nephroblastoma survival, RCR and MCR, 2006-2017.
No. of cases
5-year observed survival (%)
Median survival time
Log- rank test
p-value
Total
Events
Censored
Months
95% CI
All cases
148
64
84 (56.8%)
≤12.5%
7.8
4.4-11.3
—
Registry
0.372
PCS-MCR
69
30
39 (56.5%)
0.0%
8.5
4.9-12.2
DOH-RCR
79
34
45 (57.0%)
≤29.3%
7.8
0.3-15.4
Age group
0.565
< 1
15
4
11 (73.3%)
≤43.2%
5.8
3.1- 8.5
1 – 4
91
46
45 (49.5%)
≤6.0%
8.5
4.8-12.3
5 – 9
26
9
17 (65.4%)
≤31.2%
5.7
4.3-7.1
10 – 14
12
4
8 (66.7%)
≤64.8%
—
—
15 – 19
4
1
3 (75.0%)
≤75.0%
—
—
Sex
0.815
Male
82
37
45 (54.9%)
≤11.9%
9.7
6.3-13.1
Female
66
27
39 (59.1%)
≤13.8%
6.7
3.5- 9.1
Extent of disease
0.053
Localized
9
0
9 (100.0%)
≤100.0%
—
—
Regional
6
1
4 (80.0%)
≤50.0%
19.5
—
Distant metastasis
25
16
9 (36.0%)
0.0%
5.7
0.5-10.9
Unknown
109
47
62 (56.9%)
≤9.7%
7.8
3.6-12.0
Initial treatment
<0.001
Without treatment
0
—
—
—
—
—
With treatment
58
11
47 (81.0%)
≤33.1%
19.4
5.6-33.3
Unknown
90
53
37 (41.1%)
0.0%
4.4
2.8- 6.0
FIGURE 26 Childhood nephroblastoma overall survival, RCR and MCR, 2006-2017.
Survival was significantly different by initial treatment (p <0.001) (Figure 30). The analysis included many patients with unknown extent of disease and unknown initial treatment. Notably, no patients were recorded as receiving no treatment.
The analysis revealed no significant differences in other factors.
FIGURE 27 Childhood nephroblastoma survival by age group, RCR and MCR, 2006-2017.
FIGURE 28 Childhood nephroblastoma survival by sex, RCR and MCR, 2006-2017.
FIGURE 29 Childhood nephroblastoma survival by extent of disease, RCR and MCR, 2006-2017.
FIGURE 30 Childhood nephroblastoma survival by initial treatment, RCR and MCR, 2006-2017.
FIGURE 31 Childhood nephroblastoma survival by the registry, RCR, and MCR, 2006-2017.
Osteosarcoma
In children with osteosarcoma, the majority were diagnosed in government hospitals (76.6%) and belonged to the 10-14 (41.1%) and 15-19 years (44.8%) age groups (Table 13).
TABLE 13 Characteristics of childhood osteosarcoma, RCR and MCR, 2006-2017.
Characteristics
Osteosarcoma
(N=384)
n
%
Registry
PCS-MCR
179
46.6%
DOH-RCR
205
53.4%
Place of diagnosis
Government hospital
294
76.6%
Private hospital
62
16.1%
Private clinic
19
4.9%
Home
1
0.3%
Other hospital
8
2.1%
Age group
< 1
0
0.0%
1 – 4
7
1.8%
5 – 9
47
12.2%
10 – 14
158
41.1%
15 – 19
172
44.8%
Sex
Male
226
58.9%
Female
158
41.1%
Extent of disease
Localized
22
5.7%
Regional
20
5.2%
Distant metastasis
46
12.0%
Unknown
296
77.1%
Treatment
Treatment given
127
33.1%
Unknown
257
66.9%
Status
Alive
208
54.2%
Dead
176
45.8%
The cumulative 5-year survival rate for all osteosarcoma cases was 4.8%, with a median survival time of 11.7 months (Table 14, Figure 32).
TABLE 14 Childhood osteosarcoma survival, RCR and MCR, 2006-2017.
No. of cases
5-year observed survival
(%)
Median survival time
Log- rank test
p-value
Total
Events
Censored
Months
95% CI
All cases
384
176
208 (54.2%)
4.8%
11.7
9.3-14.1
—
Registry
0.006
PCS-MCR
179
85
94 (52.5%)
4.9%
14.3
11.6-17.0
DOH-RCR
205
91
114 (55.6%)
4.0%
9.4
7.4-11.3
Age group
0.552
< 1
0
—
—
—
—
—
1 – 4
7
2
5 (71.4%)
≤42.9%
3.3
0.0- 7.9
5 – 9
47
21
26 (55.3%)
≤8.0%
13.7
3.8-23.7
10 – 14
158
79
79 (50.0%)
3.8%
11.1
7.5-14.7
15 – 19
172
74
98 (57.0%)
7.6%
11.7
8.4-14.9
Sex
0.307
Male
226
103
123 (54.4%)
0.0%
12.9
10.0-15.9
Female
158
73
85 (53.8%)
7.4%
9.4
7.3-11.4
Extent of disease
<0.001
Localized
22
6
16 (72.7%)
23.7%
15.9
0.0-35.0
Regional
20
9
11 (55.0%)
0.0%
9.7
6.4-12.9
Distant metastasis
46
36
10 (21.7%)
0.0%
2.8
1.0- 4.7
Unknown
296
125
171 (57.8%)
3.8%
13.7
11.8-15.7
Initial treatment
<0.001
Without treatment
0
—
—
—
—
—
With treatment
127
42
85 (66.9%)
13.1%
19.2
12.7-25.8
Unknown
257
134
123 (47.9%)
2.3%
9.0
7.9-10.0
FIGURE 32 Childhood osteosarcoma overall survival, RCR and MCR, 2006-2017.
FIGURE 33 Childhood osteosarcoma survival by age group, RCR and MCR, 2006-2017.
FIGURE 34 Childhood osteosarcoma survival by sex, RCR and MCR, 2006-2017.
Childhood osteosarcoma survival was significantly better in localized and regional diseases compared to those with distant metastasis (Figure 35). The study found that patients who received treatment had improved survival rates (Figure 36). However, it is essential to note that many
patients needed more data on the extent of their disease and the initial treatment they received. Notably, no patients were recorded as not receiving any treatment.
FIGURE 35 Childhood osteosarcoma survival by extent of disease, RCR and MCR, 2006-2017.
FIGURE 36 Childhood osteosarcoma survival by initial treatment, RCR and MCR, 2006-2017.
For all the select pediatric cancers herein included, sex was not a significant survival variable.
The analysis revealed that only for osteosarcoma patients did survival appear slightly better in cases recorded by the PCS-MCR than those recorded by the DOH-RCR (Figure 37).
FIGURE 37 Childhood osteosarcoma survival by the registry, RCR, and MCR, 2006-2017.
DISCUSSION
The first report of population-based cancer survival data in the Philippines came from the IARC’s 1998 monograph ‘Cancer Survival in Developing Countries’ 14. This study primarily focused on adult cancers 14-17 and identified a concerning trend: survival rates decreased as the extent of the disease increased for all cancers studied. Improvements in cancer control and making early diagnosis and treatment more accessible remain major challenges.14-17
On childhood cancer, Redaniel et al. 18, using the US SEER and the DOH-RCR PCS-MCR 5-year survival data (2001-2005), noted that childhood leukemia and lymphoma relative survival rates were much lower in Filipinos living in the Philippines (32.9 and 47.7%) than in Asian Americans (80.1 and 90.5%) and Caucasians (81.9 and 87%). Achievement of comparable survival rates of Philippine residents lagged by 20 to >30 years compared with patients in the United States. The significant differences in survival estimates of US populations and Philippine residents highlighted the deficiencies of pediatric cancer care delivery in the Philippines. The long survival lag underlines the need for significant improvements in access to diagnostic and treatment facilities. The population-based five-year survival rates for pediatric cancer in the Philippines from 2006 to 2017 revealed critical insights into the challenges and opportunities within the country’s healthcare landscape. There were low survival rates for lymphoid Leukemia (19.9%%), Hodgkin’s lymphoma (24.0%), Burkitt’s lymphoma (16.7%), retinoblastoma (31.6%), nephroblastoma (12.5%), and osteosarcoma (4.8%). The analysis revealed survival rates that fall significantly below the WHO GICC target of 60%. This stark contrast highlights the challenges faced by the Philippines in cancer
care and control. These findings represent the survival status of Filipino pediatric cancer patients diagnosed before the implementation of the NICCA program.
This study underscores the existing healthcare disparities in Filipino pediatric cancer care. Lack of access to cost-effective and efficient diagnostic and treatment facilities, financial difficulties, and lack of awareness are the major problems faced by Filipino pediatric cancer patients.5,8,18 The current data analysis shows that most diagnoses of pediatric cancer cases happened in government hospitals. Diagnoses in government hospitals can significantly limit access to care and treatment for childhood cancers, thereby impacting cumulative survival rates. This is especially true for patients with lymphoid Leukemia, Hodgkin’s lymphoma, retinoblastoma, nephroblastoma, and osteosarcoma. The top Filipino pediatric cancers are Leukemia (lymphoid). Lymphoma (HL/ NHL), CNS neoplasms (astrocytoma), bone tumors (osteosarcoma), soft tissue sarcoma (rhabdomyosarcoma), retinoblastoma, germ cell tumor (CNS), hepatic tumor (hepatoblastoma), and nephroblastoma, in descending order of incidence (PCS-MCR, 2013-2017).19
The quality of care pediatric cancer patients receive significantly impacts their outcomes. Tertiary hospitals with pediatric oncologists, pediatric oncology units, and access to diagnostic and treatment modalities like MRI, PET-CT scan, immunophenotyping, and cytogenetics can provide more comprehensive care that may improve the survival rates of pediatric cancer patients. Osteosarcoma, for example, was noted to have a survival difference between registries, with slightly better survival for those in PCS-MCR. PCS-MCR covers four significant cities: Manila City, Quezon City, Pasay City, and Caloocan City. Critical government hospitals located in these areas include the Philippine General Hospital, National Children’s Hospital, and Philippine Children’s Medical Center, which cater to pediatric oncology cases and are end-referral hospitals; private tertiary cancer centers are also here like Manila Doctor’s Hospital, Santo Tomas Hospital and Medical Center, St Luke’s Medical Center, Chinese General Hospital, and Manila Medical Center. DOH-RCR covers Las Pinas City, Makati City, Malabon City, Mandaluyong City, Marikina City, Muntinlupa City, Navotas City, Paranaque City, Angono, Antipolo, Baras, Binangonan, Cainta, Cardona, Jala-Jala, and Montalban/Rodriguez – a larger area, but with less government and private specialty hospitals.
Implementing the DOH ALL-CCMAP and PhilHealth ALL Z packages in 2012, which provided diagnostics and drugs for patients diagnosed with acute lymphocytic/lymphoblastic Leukemia, improved the survival rates of children with this disease. This finding suggests that including such programs can positively impact pediatric cancer survival in the Philippines. Since 2022, the DOH- CCMAP and the Cancer Assistance Fund mandated by the NICCA program have provided subsidized drugs and diagnostics for other childhood cancers.
Differences in survival between age groups for lymphoid Leukemia, Hodgkin’s lymphoma, osteosarcoma, and retinoblastoma indicate the need for public campaigns to increase awareness of pediatric cancer signs and symptoms. The challenge now is reaching out to all these children for early diagnosis and prompt, complete treatment from a nationwide chain of pediatric cancer clinics.
This study found that the PBCR data for all cancer types included many cases with missing information on the disease’s extent and the initial treatment received. Hospital-based cancer registries (HBCRs) typically capture more detailed information on the extent of cancer disease and initial treatment than population-based cancer registries (PBCRs). This is crucial because the extent of the disease and the initial treatment a patient receives significantly impact their clinical outcome. It would be best if the hospitals wherein the PBCR data were collected would have themselves PBCR to feed into the PBCR for completeness of cancer data.
An initial significant limitation in the cancer survival analysis is the lack of access to the country’s death registry (Philippine Statistics Authority (PSA)), governed by the country’s Data Privacy Act. Deaths of registry cases not occurring/ recorded in the PBCR catchment area must be validated via the PSA. The Philippine Statistics Authority (PSA) already has an official process for requesting data through a formal Data Sharing Agreement. Existing collaborations with PhilHealth, the Philippine National Police, and other government agencies exemplify this process, where data is shared at no cost. A supporting mandate of the requesting agency is a prerequisite for the collaboration. NICCA Section 28 mandates the establishment of a National Cancer Registry and Monitoring System, which includes the PBCR.
Researchers underscore the significance of conducting regular PBCR survival studies.20 This highlights the importance of seamlessly integrating this data into assessing and planning the country’s cancer control efforts. It is imperative to grant PBCRs access to the national death registry, necessitating collaborative efforts to streamline regulatory processes and ensure compliance with data privacy regulations. It is recommended that we focus on ongoing capacity building for PBCRs, including training initiatives and resource provisioning, to optimize the efficiency of data collection.
Continuing cancer registry, both hospital-based and population-based, and continuing operations of pediatric cancer clinics across the country with the support of the DOH-designated CCMAP sites and Cancer Centers, all under the mandate of NICCA, would again look for the impact of these programs via a survival analysis in 2030 at the earliest.
Further, public awareness campaigns focusing on pediatric cancers should be initiated to promote early intervention and treatment-seeking behaviors. Significantly, these recommendations extend beyond research, emphasizing the importance of integrating findings into cancer control policies. Policymakers are urged to consider the study’s implications in shaping evidence-based cancer control strategies, with a focus on improving diagnostic and treatment accessibility, fostering financial support mechanisms, and developing targeted public health campaigns.
CONCLUSION
By prioritizing accessibility, awareness, and targeted healthcare interventions, the Philippines can significantly improve the landscape of pediatric cancer care, offering better outcomes for the younger population affected by this formidable disease. A multidimensional approach involving pediatric cancer advocates, communities, healthcare authorities, regulatory bodies, research institutions, and policymakers, fortified by quality cancer survival studies, is essential to driving positive advancements in pediatric oncology care and cancer control policies in the Philippines.
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DATA AVAILABILITY STATEMENTS
Data is available at the Philippine Cancer Society Office.
ETHICS STATEMENT
Ethics approval was given by SJREB of DOH.
AUTHORS CONTRIBUTION
All authors contributed to the writing of the manuscript as well as the collection of data.
FUNDING
WHO
CONFLICT OF INTEREST
The authors declare no conflicts of interest related to commercial or financial relationships.
PUBLISHER’S NOTE
This article reflects the views and findings of the authors alone and does not necessarily represent the official position of the author’s affiliated organizations, the publisher, editors, or reviewers. We encourage readers to remember that the content presented here does not constitute endorsement or approval by any of the entities above.
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Thomas Jason Chaking Ngelangel,1 Richmarie Grace Uy, 1 Stephen Lowell Ciocon, 1 Charles Cedy Lo, 1 Marc Vincent Barcelona, 1 Jaemelyn Marie Fernandez-Ramos, 1 Miriam Joy Calaguas1
1Department of Radiotherapy, Jose R. Reyes Memorial Medical Center, Rizal Avenue, Sta. Cruz, Manila
Corresponding author: Thomas Jason Chaking Ngelangel; tj_ngel@yahoo.com
ABSTRACT
Objective: To evaluate the effectiveness and safety of hypo-fractionated radiotherapy (HFRT) versus conventional radiotherapy (CFRT) postmastectomy among Filipino women with <Stage III breast cancer.
Methods: This is a cohort study on histopathological confirmed locally advanced breast cancer patients who underwent modified radical mastectomy and had negative surgical margins and <8 positive AXLN. Out of 92 patients from the following cohorts: 1) year 2014-2015, with 10 HF- PMRT patients; 2) year 2019, with 12 HF-PMRT patients and 15 CF-PMRT; 3) 2022 Jan-Mar, with 24 HF-PMRT and 31 CF-PMRT – 87 were eligible.
Patients received either HF-PMRT of 43.2 Gy in 16 fractions (2.7 Gy/fraction) to the chest wall and regional nodes or CF-PMRT with a dose of 50-50.4 Gy in 1.8-2.0 Gy/fraction to the chest wall and regional nodes with scar boost added based on high-risk factors.
Primary endpoints were overall survival, disease-free survival, locoregional recurrence, and distant metastasis control rates. Secondary endpoints included acute and late toxicities. Researchers performed an intent-to-treat analysis.
Results: HF-PMRT and CF-PMRT groups were comparable according to age, co-morbidities, clinical symptoms, and performance status; there were more menopausal women and Stage II cases in the HF-PMRT cohort. Median follow-up in months was 23.5 (range=10-98) for the HF-PMRT cohort versus 23 (range=10-39) in the CF-PMRT. All (100%) CF-PMRT patients experienced a significantly higher interruption in their radiotherapy sessions than those in the HF-PMRT cohort (68%), with a median of 8 versus three interruption days, respectively (p<0.003). The two-year overall survival rate was 86.3% for the HF-PMRT cohort and 100% for the CF-PMRT cohort, p =
0.403. There were three mortalities under the HF-PMRT arm (13.6%) and none in the CF-PMRT; all three mortalities were from the 2014-2015 cohort (1 died of brain metastasis after 26.9 months, another died of unknown cause after 47.5 months, and one died due to cardiopulmonary arrest after 17.9 months follow-up). Four-year disease-free survival rates were 68.18% in the HF-PMRT arm and 73.33% in the CF-PMRT arm, p = 0.126; 4-year distant metastasis control rates were 81.8% and 73.3%, respectively, p = 0.126. There was no reported locoregional recurrence. Acute and late toxicities were similar, mainly affecting the skin.
Conclusion: Hypo-fractionated radiotherapy (HFRT) postmastectomy shows comparable effectiveness and safety to conventional radiotherapy (CFRT) among Filipino women with <Stage III breast cancer, with fewer treatment interruptions. Despite a slightly lower two-year overall survival rate in the HFRT cohort, the disease-free survival and distant metastasis control rates were similar between the two groups, and toxicity profiles were comparable.
Keywords: Breast cancer, post-mastectomy, hypo-fractionated radiotherapy, adjuvant treatment
INTRODUCTION
The standard of care for locally advanced breast cancer patients who have undergone mastectomy is adjuvant radiotherapy to the chest wall with or without regional nodal irradiation (depending on nodal status and risk factors).
The Jose R. Reyes Memorial Medical Center (JRRMMC) Department of Radiotherapy serves at least 150 new patients annually and has a daily load of more than 30 patients. Currently, the standard for radiotherapy of breast cancer is conventional fractionated radiation therapy (CFRT), which delivers radiation in daily doses or fractions of 1.8-2.0 Gy units of absorbed radiation dose. The pivotal randomized trials, the National Comprehensive Cancer Network guidelines, and multiple international and national guidelines still advocate for CFRT to a total dose of 45-50.4 Gy with or without radiation boost to the scar. The total dose for institutions that perform scar boost Is 60-66 Gy; thus, treatment for post-mastectomy cancer patients would last 25-30 weekdays in 5-6 weeks.1
The duration of treatment for these patients has raised concerns about scheduling and logistics. Due to the large number of patients receiving and seeking treatment and the limitation in the number of patients JRRMMC can treat with the linear accelerator machine, there are instances where patients must wait 4-6 weeks before receiving treatment. The 5-6 weeks treatment period makes it hard logistically for the patients, as many reside very far from the hospital, with difficulty in their daily commute or in finding accommodations within Metro Manila.
The use of post-mastectomy radiation therapy for breast cancer patients to improve locoregional control and overall survival has been well-established in the landmark trials of Danish 82B and 82C by Overgaard et al.. 2- 3 and the British Columbia randomized trial by Ragaz et al. 4. It has become routine in treatment facilities that have the capability.
A recent trend towards hypo-fractionated dosing to, initially, whole breast radiation therapy and, to post-mastectomy patients to exploit the relatively low a/b ratio and to allow for shorter treatment times has shown non-inferiority in terms of survival, local control, and toxicity.5-7 Radiobiological experiments have shown the use of hypo-fractionated doses of radiation therapy (HFRT) to increase adverse effects on late-responding tissues, and this has always been a concern in its application, such that the use of conventionally fractionated doses of radiation therapy is still the most used.8
Several randomized trials,5-7 however, have shown hypo-fractionated doses of radiation for breast cancer patients to be of favorable efficacy and toxicity. This is particularly advantageous in low- to-middle-income countries such as the Philippines, where treatment costs and logistics concerns are prevalent.
Recently, the COVID-19 pandemic has compelled professional societies for radiation oncology, such as the American Society for Radiation Oncology (ASTRO) and the Philippine Radiation Oncology Society (PROS), to issue guidelines and statements regarding the use of hypo- fractionated treatment regimens for various cancer sites (including breast) to decrease the number of patient visits to radiotherapy facilities, to mitigate possible risk of virus exposure and spread, especially among the vulnerable cancer population.10
METHODS
This JRRMMC Philippine observational cohort study compared the effectiveness and safety of hypo-fractionated post-mastectomy radiation therapy versus conventionally fractionated post- mastectomy radiation therapy among <Stage III breast cancer patients.
Study Subjects
Study subjects were selected based on specific inclusion and exclusion criteria. Eligible patients had undergone mastectomy for histopathologically confirmed breast cancer with negative margin resection. They must have had lymph node dissection (including sentinel lymph node biopsy) with fewer than eight positive lymph nodes confirmed histopathologically. Patients who consented to participate in the study were included. However, individuals were excluded if they had internal mammary lymph node metastasis, distant metastasis, any active collagen disease, or active double primary cancer (except for carcinoma in situ and bilateral breast cancer). Additional exclusion criteria included concurrent chemoradiotherapy, previous chest irradiation, pregnancy, and potential pregnancy.
The study included two cohorts: patients from 2014-2015 who received hypofractionated radiotherapy (HFRT) post-mastectomy, and patients from 2019 and January-December 2022 who received either conventional fractionated radiotherapy (CFRT) or HFRT post-mastectomy. Researchers thoroughly explained the possible benefits and side effects of both CFRT and HFRT to the patients. Patients were given the choice between CFRT and HFRT, and their consent was obtained accordingly.
Ethical Considerations
The JRRMMC Ethics Committee approved this study. Patients were asked for their consent, and patient confidentiality was upheld.
Treatment Protocol
The radiation treatment protocol delivers a total dose of 43.2 Gy to patients with negative surgical margins, administered in 16 fractions over 22 days to the chest wall and supraclavicular region. The internal mammary lymph nodes are not included in the radiation field. The radiation sources used are 4-6 MV X-rays or Cobalt-60 X-rays. A tangential irradiation method aligning posterior margins is employed. Treatment planning aims to achieve target dose homogeneity within ±7% of the Planning Target Volume (PTV), adhering to this principle as closely as possible. The radiation field primarily focuses on the chest wall, following established guidelines. Importantly, for all patients, the thickness of the lung field within the radiation field must not exceed 3 cm, ensuring minimal lung tissue exposure.
Borders of radiation field for the chest wall
Inner margin
Midline of sternum
Outer margin
Middle axillary line
(1.5-2 cm outside palpable mammary glands)
Upper margin
Between the upper edge of the acromial extremity of the clavicle and the lower edge of the extremities sternalis claviculae
First costal interspace
Lower margin
1-2 cm from the lower edge of contralateral breast borders for the radiation field of the supraclavicular area
Inner margin
The midline extends from the first costal interspace to the thyroid-cricoid groove, and the medial to the sternocleidomastoid muscle includes the lower
lymph nodes of the cervical chain.
Outer margin
From the acromioclavicular joint, bisecting the humeral head, to exclude as
much of the shoulder as possible.
Upper margin
Extend laterally across the neck and trapezius to the acromial process,
ensuring the entire supraclavicular fossa is included visually.
Lower margin
First, costal interspace, abutting the tangential breast field
Radiotherapy Regimen Given
Conventional Radiotherapy
Hypo-fractionated Radiotherapy
Total Dose
50 Gy
43.2 Gy
Dose per fraction
2 Gy
2.7 Gy
Number of fractions
25 fractions
16 fractions
Tumor bed boost
10 Gy (2 Gy per fraction for five
fractions)
None
Overall treatment
days
33 days;40 days (if with boost)
22 days
A scar boost was administered to patients with high-risk factors in the conventionally fractionated arm for dose and fractionation. These factors included age under 50, positive axillary nodes, lympho-vascular invasion, or close margins. However, patients in the hypo-fractionated arm did not receive any scar boost. Regarding the irradiation position, patients were immobilized using a breast board in a supine position with the affected side’s upper limb raised. The radiation sources employed were 6 MV X-rays and Cobalt-60 X-rays. The irradiation methods varied by target area: a tangential irradiation method aligning posterior margins were used for the chest wall and tumor bed boost, while the supraclavicular field was treated with a single anteroposterior (AP) field. Treatment planning aimed to achieve target dose homogeneity within ±7% of the Planning Target Volume (PTV), adhering to this principle as closely as possible.
Combination Therapy
Concurrent chemotherapy was not allowed during radiation therapy. However, concurrent endocrine therapy was allowed. Adjuvant or neoadjuvant systemic therapy followed NCCN guidelines at the discretion of the medical oncologist.1
Cancellation Criteria for the Protocol
A patient may be removed from the study for several reasons: if they are found to be ineligible based on inclusion or exclusion criteria after initial registration; if concurrent chemotherapy is administered, which could interfere with the study’s treatment protocol; if the trial is discontinued due to an adverse event that poses unacceptable risks to participants; if a patient withdraws their consent for participation, exercising their right to leave the study at any time; or if a physician determines that treatment needs to be discontinued for medical reasons, prioritizing the patient’s safety and well-being over the study’s objectives.
Data collection
Patient data were collected using case report forms (patient demographic profile and eligibility, disease and treatment profile, radiotherapy and compliance to treatment, other cancer therapy, adverse events, and follow-up after one-month post-RT, and every three months after that looking for radiation toxicities, disease progression, and survival), reviewing patient medical records.
Assessment of Effectiveness
The assessment of effectiveness in this study encompasses several key aspects. Locoregional recurrence is any mass observed at the primary site or regional lymph nodes following complete breast treatment, detected through clinical examination or imaging. Evaluation occurs every three months in the first year, biannually from years two to five, and annually thereafter. The evaluation methods include clinical breast examinations, mammography/ultrasound, and pathology assessments when necessary. Disease progression is identified by distant metastasis or locoregional recurrence, documented through symptoms, physical examinations, and imaging.
Survival analysis focuses on two primary metrics: overall survival and disease-free survival. Overall survival is measured from the start of radiotherapy to death from any cause, while disease- free survival spans from the initiation of radiotherapy to disease progression. This interim analysis requires a minimum of one year of survival data to provide meaningful insights into the treatment’s effectiveness and patient outcomes.
Assessment of Toxicity
Acute toxicities for each patient were serially monitored during and after treatment (within 90 days from the beginning of treatment). Evaluation of acute toxicities was done once a week during treatment and one month and three months after the end of treatment. A chest x-ray was performed as needed. Hematological toxicities were assessed according to the NCI/CTC version 4.0.24. The researchers assessed non-hematological toxicities according to the RTOG acute radiation morbidity scoring system..25
Late toxicities for each patient were periodically monitored after treatment (>91 days after treatment). Regions observed were the skin, subcutaneous tissue, lungs, and heart. Late toxicities were assessed every three months for the first year, every six months for the 2nd year after treatment, and at 3rd-5th year once a year. Data assessors use the RTOG/EORTC late radiation morbidity scoring scheme, the Common Terminology Criteria for Adverse Events v4.0 (CTCAE)24, and the LENT-SOMA scale.26-29 For a left-sided breast cancer patient, two- dimensional echocardiography was requested, whereas a 12-lead ECG was requested for a patient with right-sided breast cancer. A chest x-ray was done accordingly.
Statistical Analysis Sample Size Calculation
The sample size calculator from the Cancer Research and Biostatistics (CRAB) website of the
Southwest Oncology Group (SWOG) Statistics and Data Management Center was used,30 assuming a computation for a one-arm cohort study.
FIGURE 1 Sample Size Calculation based on software from the Cancer Research and Biostatistics Website from the Southwestern Oncology Group.
To compute the necessary sample size in a one-arm non-parametric survival study for Kaplan- Meier survival curve analysis, a 3-year accrual time with a four-year follow-up time was used. The alpha was set at 0.05. The null survival probability was set at 0.65, which was the 5-year overall survival rate of post-mastectomy radiation therapy patients from the Danish 82B and 82C trials by Overgaard et al. (1990)2.3. Alternative survival probability was set at 0.832 based on the 83.2% 5- year overall survival rate of the Sun et al. (2017)15, b or power of the study was set at 0.80, and the computed sample size was 39 with an approximate lower critical value of 0.51 and an approximate upper critical value of 0.82; expected attrition rate was 15%. Attrition rate was compensated using the formula: sample size x [1/(1-attrition in decimal)]. A final sample size of 46 was, thus, computed; this sample size was used for both HFRT and CFRT cohorts (46 each).
Data Analysis (Preliminary)
Data was encoded and analyzed using Microsoft Excel and STATA 15.0 statistical software. All valid data were included in the analysis. The null hypothesis was rejected at the 0.05 α-level of significance.
Descriptive statistics was used to summarize the general and clinical characteristics of the patients: frequency and proportion for categorical variables (nominal/ordinal), mean and standard deviation for normally distributed interval/ratio variables such as age, and median and range for non- normally distributed interval/ratio variables such as time from the start of therapy to mortality.
The mean, frequency, and median differences between groups were determined using the independent sample T-test, Fisher’s exact/chi-square test, and Mann-Whitney U test, respectively. The Kaplan-Meier survival estimates method was used to construct curves for overall and disease- free survival, locoregional recurrence, and distant metastasis control. Outcome parameters were estimated up to 4 years.
RESULTS
A total of 87 women who underwent mastectomy for breast cancer, with an average age of 49.90
± 11.57 years, were included in the study; 46 underwent HFRT and 41 CFRT. The HFRT group was more of the menopausal group (78% vs 44%) [p = 0.0017] (Table 1). The two groups were comparable according to age, co-morbidities, performance status, clinical symptoms (Table 1), molecular subtype, laterality, and tumor site (Table 2), adjuvant drug therapy (Table 3).
Three (3) patients were lost to follow-up: two (2) in the HFRT cohort and one (1) in the CFRT cohort.
TABLE 1 Demographic profile of post-mastectomy breast cancer patients who underwent HFRT or CFRT (n=87).
Total (n=87)
HFRT (n=46)
CFRT
(n=41) p-value
Mean ± SD; Frequency (%)
Age, years
49.90 ± 11.57
51.24 ± 12.06
48.39 ± 10.94
0.2537*
Menopause
54 (62.07)
36 (78.26)
18(43.90)
0.0017†
Performance status
–
0 (Fully active)
93 (100)
46 (100)
46 (100)
1
1
1
0
2
0
0
0
Concomitant disease
Asthma
1 (1.14)
1 (2.17)
0
>0.999†
Diabetes
16 (18.39)
7 (15.22)
9 (21.95)
>0.580†
Hypertension
31 (35.63)
17 (36.96)
14 (34.15)
0.826†
Others
5 (5.75)
3 (6.52)
2 (4.89)
>0.999†
Clinical symptoms
Palpable mass
87 (100)
46 (100)
41 (100)
–
Pain
3 (3.45)
0
3 (7.32)
0.101†
Lymph node swelling
0
0
0
–
Discharge
0
0
0
–
Others
1 (1.15)
0
1 (2.44)
0.471†
Statistical tests used: * – Independent sample t-test; † – Chi-square/ Fisher’s Exact test
The most common histopathologic type was ductal carcinoma (98%) (Table 2). Of these, 12 patients (13.79%) were diagnosed with both invasive ductal carcinoma (IDC) and ductal carcinoma in situ (DCIS). Of 72 women with purely IDC, 41 (89.13%) and 31 (75.61%) received HFRT and CFRT, respectively. Of 12 with in situ and invasive ductal carcinoma, 4 (8.70%) had HFRT and 8 (19.51%) CFRT. Those with HFRT had more invasive cancer than those with CFRT (p=0.013). However, both cohorts were comparable in the presence of high-risk factors (Table 2).
Over half of the patients were luminal-HER2neu negative (57.47%). Fourteen patients were HER2neu positive, and five were triple negative.
All patients had unilateral breast cancer, typically in the upper outer quadrant (65.52%). The patients who received HFRT had more Stage IIA and IIB patients than those in the CFRT group, who mainly were Stage IIIA and Stage IIIB (p = 0.04).
TABLE 2 Histopathologic profile of post-mastectomy breast cancer patients who underwent HFRT or CFRT (n=87).
Total (n=87)
HFRT (n=46)
CFRT (n=41)
p-value
Frequency (%)
Histopathologic type
0.013†
Invasive ductal carcinoma
72 (82.76)
41 (89.13)
31 (75.61)
IDC, DCIS
12 (13.79)
4 (8.70)
8 (19.51)
IDC, DCIS, Invasive papillary
carcinoma
1 (1.15)
0
1 (2.44)
Invasive lobular carcinoma
1 (1.15)
1 (2.17)
0
Tubular carcinoma
0
0
0
Medullary carcinoma
0
0
0
Mucinous carcinoma
1 (1.15)
0
1 (2.44)
Others
0
0
0
Subtype
0.158†
Luminal-HER2 neg
50 (57.47)
29 (63.04)
21 (51.22)
Luminal-HER2 pos
17 (19.54)
14 (30.43)
3 (7.32)
HER2neu positive
14 (21.62)
5 (10.87)
9 (21.95)
Triple-negative
5 (5.41)
1 (2.17)
4 (9.76)
Unknown
1 (2.7)
0
1 (2.44)
Laterality
0.514†
Right
41 (47.13)
27 (58.70)
14 (34.15)
Left
46 (52.87)
19 (41.30)
27 (65.85)
Both
0
0
0
Tumor site
0.395†
Upper-inner quadrant
2 (2.30)
0
2 (4.88)
Lower-inner quadrant
5 (5.75)
1 (2.17)
4 (9.76)
Upper-outer quadrant
57 (65.52)
31 (67.39)
26 (63.41)
Lower-outer quadrant
20 (22.99)
13 (28.26)
7 (17.07)
Central portion
3 (3.45)
1 (2.17)
2 (4.88)
TNM stage
0.040†
IIA: T0/1 N1 M0, T2 N0 M0
4 (4.59)
4 (8.69)
0
IIB: T2 N1 M0
30 (34.48)
19 (41.30)
11 (26.83)
IIIA: T0/1/2 N2 M0, T3 N1/2 M0
36 (41.38)
17 (36.96)
19 (46.34)
IIIB: T4 N0/1/2 M0
17 (19.54)
6 (13.04)
11 (26.83)
IIIC: AnyT N3 M0
0
0
0
Pretreatment evaluation
0.446†
Not done
1 (1.15)
1 (2.17)
0
Mammography
36 (41.38)
22 (47.83)
14 (34.15)
Mammography and ultrasound of
the breast
7 (8.05)
2(4.34)
5 (12.19)
Total (n=87)
HFRT (n=46)
Frequency (%)
CFRT
(n=41) p-value
Ultrasound for breast
18 (20.69)
8 (17.39)
10 (24.39)
CT scan
9 (10.34)
6 (13.04)
3 (7.32)
MRI for breast
0
0
0
Others
16 (18.39)
7 (15.22)
9 (21.95)
High-risk factor
0.681†
Age<50
42 (48.28)
20 (43.48)
22 (53.66)
Positive axillary node
5 (5.75)
2 (4.35)
3 (7.32)
Age<50
16 (18.39)
7 (15.22)
9 (21.95)
Lymphovascular invasion
1 (1.15)
1 (2.17)
0
Close margins
3 (3.45)
0
3 (7.32)
No high-grade factors
20 (22.99)
16 (34.78)
4 (9.76)
Statistical tests used: * – Independent sample t-test; † – Chi-square/ Fisher’s Exact test
All patients (100%) who underwent CFRT experienced an interruption in their radiotherapy sessions, significantly higher than in the HFRT group (71.74%). The duration of interruption was also longer in the CFRT group (median eight vs three days) [p < 0.003].
Endocrine therapy, adjuvant therapy, and targeted therapy were comparable between the two groups.
TABLE 3 Treatment profiles of post-mastectomy breast cancer patients by type of radiotherapy fractionation (n=87).
Total (n=87)
HFRT (n=46)
Frequency (%)
CFRT
(n=41) p-value
Chest wall irradiation
87 (100)
46 (100)
41 (100)
–
Dose
Schedule
Supraclavicular fossa
85 (97.70)
44 (95.45)
41 (100)
>0.999†
Dose
43.2
46 (52.87)
46 (100)
0
50
3 (3.45)
0
3 (7.32)
60
38 (43.68)
0
38 (92.68)
Dose
16
46 (52.87)
46 (100)
0
25
3 (3.45)
0
3 (7.32)
30
38 (43.68)
0
38 (92.68)
Interruption of radiotherapy
74 (85.06)
33 (71.74)
41 (100)
0.0001†
Days
5.5 (1–24)
3 (1–9)
8 (5–24)
<0.003‡
Neoadjuvant chemotherapy [n=86]
25 (29.07)
12 (13.95)
13 (15.12)
0.638†Total (n=87)
HFRT (n=46)
Frequency (%)
CFRT
(n=41) p-value
Endocrine chemotherapy [n=85]
71 (83.53)
39 (45.88)
32 (37.65)
0.580†
Adjuvant chemotherapy [n=86]
70 (80.40)
37 (43.02)
33 (38.37)
>0.999†
Targeted therapy [n=86]
30 (34.88)
16 (18.60)
14 (16.28)
>0.999†
Statistical tests used: † – Chi-square/ Fisher’s Exact test; ‡ – Mann-Whitney U test.
None of the patients in each cohort experienced any locoregional recurrence. Six patients in the CFRT cohort had distant metastases, whereas four in the HFRT cohort had distant metastases (Table 4).
TABLE 4 Outcomes of post-mastectomy breast cancer patients who underwent radiotherapy (n=87).
Total (n=87)
HFRT (n=46)
CFRT (n=41)
p-value
Frequency (%); Median (Range)
Efficacy
Primary tumor
recurrence
0
0
0
–
Lymph node
0
0
0
–
Distant metastasis
10 (11.49)
4 (8.70)
6 (14.63)
0.690†
The distant metastasis control rate was 91.30% for the HFRT arm and 85.37% for the CFRT arm, p>0.05 (Figure 2). Three patients with distant metastases in the HFRT arm were from the 2014- 2015 HFRT cohort.
FIGURE 2. Distant control estimates of post-mastectomy breast cancer patients who underwent radiotherapy(n=87) limiting follow-up to 60 months.
Three out of the 87 patients died, all from the 2014-2015 HFRT cohort (Table 4). Causes of death include one (1) patient with progression of brain metastases at 26.9 months, one (1) died of unknown causes after 47.5 months, and one (1) died of cardiopulmonary arrest after 17.9 months of follow-up. The overall survival rate was 93.48% for the 2014-2015 & 2019 & 2022 Jan-Mar HFRT cohorts and 100% in the 2019 & 2022 Jan-Mar CFRT cohorts, p = 0.403 (Figure 3).
FIGURE 3 Overall survival estimates of post-mastectomy breast cancer patients who underwent radiotherapy (n=87).
Disease-free survival rate was 84.78% in the HFRT arm and 85.37% in the CFRT arm, p = 0.126 (Figure 4).
FIGURE 4 Disease-free survival estimates of post-mastectomy breast cancer patients who underwent radiotherapy(n=87), limiting follow-up to 60 months.
Acute and late toxicities were comparable between the two arms. Grade 1 acute skin toxicities were reported in 95.65% of the HFRT group and 85.37% of the CFRT group. Two patients (4.35%) had Grade 2 skin toxicity in the HF-PMRT group and five (12.20%) in the CFRT group, p = 0.703 (Table 5a).
TABLE 5A Adverse Event Outcomes of post-mastectomy breast cancer patients who underwent radiotherapy (n=87).
Total (n=87)
HFRT (n=46)
CFRT (n=41)
p-value
Frequency (%); Median (Range)
Findings of acute adverse effect
Skin
0.703†
Grade 1
79 (90.80)
44 (95.65)
35 (85.37)
Grade 2
7 (8.05)
2 (4.35)
5 (12.20)
There were no adverse effects on the breast, lung, or heart. There were no significant differences in late toxicities between the two arms (Table 5b). The HFRT cohort had six patients with RTOG Grade 1 late skin toxicities, and one patient had Grade 3 late skin toxicity; the CFRT cohort had 1 case of Grade 1 late skin toxicity, p = 0.196. Grade 1 late subcutaneous toxicities were in the HFRT arm (4.35%) and the CFRT arm (4.88%), p = 0.999. Late adverse events were reported in eight patients with skin atrophy, four patients with subcutaneous induration, and one patient with Grade 1 toxicity on the breast. The numerically higher number of Grade 1 late skin toxicities were from the 2014-2015 HFRT cohort, with a more extended follow-up period than the 2019 and 20-22 cohorts from which the CFRT patients came. A five-year follow-up of the cohorts is still ongoing.
DISCUSSION
This JRRMMC Philippine observational cohort study interim analysis (at one year or more follow- up) shows that all the effectiveness endpoints (survival, locoregional recurrence, and distant metastasis control) and safety endpoints (acute and late toxicities) were comparable between the HF-PMRT and CF-PMRT. HF-PMRT promises to be a favorable treatment strategy for breast cancer.
The Chinese HFRT post-mastectomy randomized trial15 provided the most information on this. It compared a dosing regimen of 43.5 Gy in 15 fractions over three weeks. The 5-year cumulative incidence of locoregional recurrence was 8.3% for the HFRT arm and 8.1% for the CFRT arm, well within the pre-specified level of non-inferiority (p <0.0001). There was no significant difference in the 5-year overall survival (84% vs 86%) and 5-year disease-free survival (74% vs 70%).
The FAST Forward Trial23 compared three arms: (1) 26 Gy in 5 fractions, (2) 27 Gy in 5 fractions, and (3) 40 Gy in 15 fractions. It noted that the 5-year incidence of ipsilateral breast tumor recurrence was within the pre-specified level of non-inferiority for both experimental arms. However, most of the patients in the study underwent whole breast irradiation rather than post- mastectomy RT (PMRT), making the Beijing HF-PMRT trial15 the more relevant support literature of this Philippine JRRMMC study.
The two cohorts in this JRRMMC Philippine study were comparable in acute and late toxicities. None of the patients experienced Grade 4 toxicities or higher. The numerical difference in late skin toxicities between cohorts may be due to the longer follow-up of the 2014-2015 HFRT cohort.
The Chinese randomized HFRT postmastectomy trial15 noted a statistically significantly higher rate of Grade 3 acute toxicities in the CFRT arm.
Most data on hypofractionation are for whole breast irradiation, and several studies have shown equivalent or better acute and late toxicity profiles with hypofractionation31.
Detecting and grading toxicity is highly important in trials that concern altered fractionation, as the theoretical disadvantage of hypofractionation is an increased rate of late toxicities5-6,8. Based on this interim JRRMMC Philippine study, that of the Chinese RCT15, and the pivotal trials5-7,22 of the hypo-fractionated WBI era, this has not been the case so long as the radiation therapy is delivered properly.
There is thus a possible increase in the adoption rate of HFRT postmastectomy, especially in situations like the COVID-19 pandemic, the distance of RT facilities, and productivity loss during long treatment periods.
HFRT post-mastectomy, which has a lower overall treatment time, may reduce treatment interruptions due to external factors or factors out of the control of the treatment facility. Unintended treatment interruptions can prolong overall treatment time, which has been known to lead to inferior clinical outcomes. In a 2017 retrospective study, Rudat et al. compared adjuvant treatment for breast cancer between hyperfractionated radiotherapy (HFRT) and conventional fractionation radiotherapy (CFRT). They had shown that the HFRT arm resulted in better patient compliance, with the fractionation regimen being the only independent significant prognostic factor for compliance. In this JRRMMC Philippine study, treatment interruptions in the CFRT arm were significantly higher.
Breast cancer is still the cancer with the highest incidence globally and in the Philippines, and most Filipino breast cancer patients still present with locally advanced breast cancer and most likely will undergo modified radical mastectomy. This JRRMMC Philippine study’s findings add to the growing body of research investigating the similar clinical efficacy of HFRT and CFRT following mastectomy. The study’s findings suggest that HFRT following mastectomy could be adopted as a future standard treatment. This adoption of HFRT would have significant implications for patients, their families, and entire healthcare systems. The shorter overall treatment time can decrease the indirect costs shouldered by patients through their daily commutes to the radiotherapy center, especially those from remote provinces. Healthcare systems may be able to experience a reduction in expenses due to the fewer days of treatment needed to treat breast cancer patients, which is the cancer type with the highest number of cases in Philippine radiotherapy centers.
As the study was non-randomized, the comparability between the intervention and control groups was limited. Selection and time period bias might affect the generalizability of results, as might the small sample size. The study is limited to a single government institution.
CONCLUSION
This study comparing hypofractionated radiotherapy (HFRT) with conventional fractionated radiotherapy (CFRT) in Filipino women with stage III or lower breast cancer who underwent mastectomy has yielded promising results. The effectiveness of HFRT appears comparable to CFRT, with no significant differences observed in locoregional recurrence, disease-free survival, or overall survival rates between the two groups. Notably, HFRT demonstrated advantages in terms of treatment adherence, with significantly fewer interruptions and shorter durations of interruptions compared to CFRT.
In terms of safety, both HFRT and CFRT showed similar profiles of acute and late toxicities, with most adverse events being mild (Grade 1) and manageable. The slightly higher number of late skin toxicities observed in the HFRT group may be attributed to the longer follow-up period for this cohort. These findings suggest that HFRT could be a viable alternative to CFRT in this patient population, potentially offering benefits such as improved treatment compliance and reduced burden on healthcare resources without compromising oncological outcomes or patient safety. However, longer-term follow-up data, particularly for the more recent cohorts, will be crucial to confirm these initial findings and to assess any potential differences in late effects between the two treatment approaches.
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Sun GY, Wang SL, Song YW, Jin J, Wang WH, Liu YP, et al. Hypofractionated Radiation Therapy After Mastectomy for the Treatment of High-Risk Breast Cancer: 5-Year Follow-Up Result of a Randomized Trial. Int J Radiat Oncol Biol Phys. 2017;99(2):S3-4.
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DATA AVAILABILITY STATEMENTS
Not publicly available
ETHICS STATEMENT
The Ethics Review Board/Committee of Jose R. Reyes Memorial Medical Center approved the study.
AUTHORS CONTRIBUTION
TJCK, RGU, MVB, JMF, data curation, investigation, methodology, software, validation, writing – original draft, writing – review & editing;
TJCK, software, writing – review & editing;
TJCK, RGU, MVB, JMFR, investigation, writing – review & editing; TJCK, RGU, CCL, MVB, JMFR, investigation, writing – review & editing; TJCK, SLC, resources, writing – review & editing;
TJCK, SLC, methodology, writing – review & editing; TJCK, SLC, resources, writing – review & editing; TJCK, writing – original draft;
TJCK, RGU, SLC, writing – review & editing;
TJCK, RGU, SLC, resources, writing – review & editing; TJCK, RGU, SLC, writing – review & editing;
TJCK, JMFR, MJC, conceptualization, data curation, funding acquisition, methodology, supervision, validation, writing – original draft, writing – review & editing
FUNDING
This research received no external funding.
CONFLICT OF INTEREST
The authors declare no conflicts of interest related to commercial or financial relationships.
PUBLISHER’S NOTE
This article reflects the views and findings of the authors alone and does not necessarily represent the official position of the author’s affiliated organizations, the publisher, editors, or reviewers. We encourage readers to remember that the content presented here does not constitute endorsement or approval by any of the entities above.
Similarly, any products or services mentioned within this article are for informational purposes only. The publisher recommends that readers conduct independent evaluations before making any decisions, as the publisher does not guarantee or endorse any products or services mentioned.
Lawrence Raymond Mariano,1 Eddie Lim, 1,2 and Nicole Patricia Hui1,3,4
1 Department of Nuclear Medicine & PET/CT Center, The Medical City Ortigas, Pasig City 2
Department of Molecular Imaging and Radionuclide Therapy, Rizal Medical Center, Pasig City, 3 Department of Nuclear Medicine, Manila Doctors Hospital, Manila, 4 Department of Nuclear Medicine, ManilaMed (Medical Center Manila), Manila
Corresponding author: Lawrence Raymond Mariano; lawrencevmariano@gmail.com
ABSTRACT
Objective: To compare the diagnostic performance of blue dye and combined blue dye with lymphoscintigraphy for sentinel lymph node (SLN) localization in early-stage breast cancer patients.
Methods: The researchers retrospectively reviewed 350 patients who underwent SLN biopsy. The patients were divided into two groups: those who received blue dye only (N = 167) and those who received a combination method (N = 183).
Results: The combined method showed significantly improved sensitivity (97.0% vs. 82.5%), accuracy (96.0% vs. 80.3%), and reduced false negative rates (3.0% vs. 17.5%) compared to blue dye alone (p < 0.001). Specificity was comparable between groups (33.3% vs. 34.6%). Compared to blue dye alone, the combined method yielded superior performance in patients with previous excision. For patients who received neoadjuvant therapy, the combined method achieved 100% accuracy and no false negatives, while blue dye alone showed lower accuracy (70.6%). However, the small sample size for this subgroup limits definitive conclusions.
Conclusion: The combined method shows potential benefits in improving SLN localization accuracy, particularly in patients with previous excision. Further research in larger populations is needed to validate these findings further.
Keywords: Sentinel Lymph Node (SLN), breast cancer, blue dye, lymphoscintigraphy, diagnostic accuracy, sensitivity, specificity, false negative rate, neoadjuvant therapy, excision biopsy
INTRODUCTION
Breast cancer remains one of the most prevalent malignancies worldwide.1 In the Philippines, it is the leading cause of cancer mortality and morbidity, with around 27,000 newly diagnosed cases in 2020 alone.2 An essential aspect in the early management of this disease is axillary lymph node staging. Identification and biopsy of sentinel lymph nodes (SLNs) affect adjuvant treatment decisions and eliminate the need for axillary lymph node dissection (ALND), thus significantly reducing post-operative complications like lymphedema, limitation of shoulder motion, and arm paresthesia.
Several methods can be used to localize sentinel lymph nodes. While more novel techniques, such as indocyanine green fluorescence imaging, are emerging,3 blue dye injection and lymphoscintigraphy using radioactive colloid are the most commonly utilized in local and global settings. Both agents are preoperatively injected into the breast. Identifying lymph nodes using the
blue dye technique has shown good overall efficacy, with identification rates ranging from 95 to 98% and false negative rates of approximately 13%.4-6 In the same manner, sentinel node localization using lymphoscintigraphy alone has also shown good overall efficacy of 91.4%, with false negative rates of 7.4%. However, the combination of blue dye and radioactive colloid in sentinel node localization shows excellent efficacy, with detection rates approaching 98% to 100%.7-9
The results of research comparing the two techniques are limited and conflicting. Kim Giuliano and Lyman’s systematic review results showed significantly higher SLN identification rates and lower false negative rates when comparing the combination technique to either blue dye or radiotracer alone (p<0.05).10 In another meta-analysis, Liu et al. also found that the identification rate of the combination method was superior to that of using blue dye alone.11 Finally, Pesek et al. reported a significantly lower false negative rate of using the combination technique (5.9%) versus dye-only (8.6%; p=0.018).12 In contrast, a randomized controlled trial conducted by Gupta and colleagues found that although the combination technique yielded higher sensitivity (83.33%) and specificity (91.67%) than using blue dye alone (sensitivity: 75%, specificity: 95.45%), the difference was not statistically significant (p>0.05). False negative rates in this study were also comparable (8.6% vs. 4.3%, p>0.05).13 Similarly, Varghese et al. found no significant difference (p=0.354) in the detection rate of blue dye alone (96.5%) and the combination of tracer and dye (98.7%).14 Significant differences in these studies’ design and localization methodology, such as the dose of blue dye or radiotracer and the injection technique, may have contributed to the opposing results.
Both techniques rely heavily on the lymphatic drainage of the breast, so practitioners may encounter difficulty in SLN localization for patients who underwent neoadjuvant chemotherapy or excision biopsy of the same breast. Localization may be more difficult due to fibrosis, fat necrosis, and granulation tissue formation, which may alter lymphatic drainage patterns.15 For patients with neoadjuvant treatment, Chirappapha et al. found only an 85.71 % detection rate using either blue dye or radiocolloid and false negative rates of 30 – 40 %.16 When utilizing dye and radiocolloid, Tee et al. found identification rates of 78-93% and false negative rates of 5-20%.15 Meanwhile, Coskun et al. reported an 83% identification efficiency and 15.7% false negative rate when utilizing blue dye for patients with previous excision biopsy of the same breast.17 However, published data regarding the combination technique has yet to be reported in this subset of patients. As such, the optimal localization method for these subgroups of patients needs to be studied further.
Objectives
The general objective of this study is to evaluate the comparative effectiveness of sentinel lymph node localization using blue dye alone versus combined blue dye with lymphoscintigraphy in patients diagnosed with breast cancer. Specifically, the study aims to compare the diagnostic accuracy, sensitivity, specificity, and false negative rates of these two localization methods, and to assess for statistically significant differences in these parameters. Furthermore, the research will evaluate whether the performance differences between the two methods vary among patients with and without a history of neoadjuvant therapy. Additionally, the study will determine if there are significant differences in performance between the two methods in patients with a history of excision biopsy of the same breast compared to those without such history. Through these objectives, the study seeks to provide comprehensive insights into the efficacy of these localization
techniques in various clinical scenarios, potentially informing best practices in breast cancer management.
Definition of Terms
Sentinel lymph node – first lymph node/nodes that receives lymphatic drainage from the tumor
Blue dye – chemical agent (PBV, isosulfan blue, or methylene blue) injected near tumor site to identify / stain lymph nodes
Lymphoscintigraphy – Nuclear Medicine procedure used to visualize lymphatic drainage of tumor via injection of radioactive colloid
Sentinel lymph node biopsy (SLNB) – a surgical procedure performed to assess the presence of cancer cells in lymph nodes; involves the injection of blue dye and/or radioactive colloid that guides the surgeon in localizing the sentinel nodes during surgery
Axillary lymph node dissection (ALND) – surgical removal of axillary lymph nodes via incision in the axilla or as part of mastectomy for women with breast cancer
METHODS
Population and Sample
Researchers conducted a retrospective cohort study involving patients who underwent breast sentinel lymph node (SLN) localization through blue dye alone or in combination with lymphoscintigraphy at The Medical City Ortigas from January 1, 2018, to December 31, 2022. They computed sample sizes using G Power software (α = 0.05, power = 0.95). The overall analysis required a minimum of 134 patients, while each subgroup analysis required at least 210 samples (d = 0.5, allocation ratio = 1). Records were then gathered through convenience sampling with the following criteria:
Inclusion and Exclusion Criteria
This study will include patients diagnosed with early-stage breast cancer who underwent surgical procedures with sentinel lymph node (SLN) localization using either blue dye alone or combined with lymphoscintigraphy. To ensure the integrity and completeness of the data analysis, patients with incomplete medical records or missing data necessary for this study will be excluded. This includes, but is not limited to, missing information on localization methods, lymph node status, or other relevant clinical data. By adhering to these inclusion and exclusion criteria, the study aims to maintain a focused and reliable dataset for comparing the effectiveness of the two SLN localization methods in breast cancer patients.
Data collection
In this study, researchers utilized multiple data sources to gather comprehensive patient information. They accessed electronic records through the ArcusAir patient database and Laboratory Information System (LIS) to collect patient demographics, medical history, operative reports, and histopathological data. Additionally, they reviewed hard copies of histopathologic records from 2018 to 2022 to ensure completeness. The data gathered from these sources included patient demographics (age and sex), medical history (focusing on neoadjuvant therapy and previous breast surgery), tumor characteristics (laterality, size, and histology), the specific localization technique used (blue dye alone or combined with lymphoscintigraphy), the number of submitted lymph nodes and non-nodal tissues, and the lymph node status (positive or negative) for
both localization methods. This thorough data collection approach aimed to provide a comprehensive dataset for analyzing the comparative effectiveness of the two sentinel lymph node localization techniques in breast cancer patients.
Data management
All collected data were de-identified using the patient’s surgical pathology (SP) number and stored securely in a password-protected Microsoft Excel spreadsheet. Data was categorized based on the localization method (blue dye vs. combined). Researchers categorized the data based on the localization method used (either blue dye or combined) as “blue dye positive and/or radiotracer positive,” “radiotracer positive only,” “blue dye positive only,” or “blue dye and radiotracer negative” based on their histopathologic and radiotracer findings.
Data privacy and confidentiality
All patient data were anonymized using the surgical pathology (SP) number, a unique identifier only accessible within the Department of Laboratory Medicine and Anatomic Pathology. No other personal identifiers were collected or stored. Data was stored securely in a password-protected Microsoft Excel spreadsheet on the principal investigator’s computer. A strong password and two- factor authentication restrict access to the computer.
This study was conducted strictly with the Data Privacy Act of 2012 (RA 10173) and the ethical guidelines established by the Declaration of Helsinki. The Medical City Institutional Review Board (IRB), through the hospital’s Clinical and Translational Research Institute (CTRI), approved the study before data collection began. The Department of Laboratory Medicine and Anatomic Pathology also obtained written permission for data access.
Analysis
The researchers used descriptive statistics to analyze patient demographics, tumor characteristics, and the distribution of localization methods employed. They created two-by-two tables for each group (blue dye and combined localization). The rows represented the tissue’s localization status (positive/negative) based on the specific method used (blue dye or combined). The columns distinguished between lymph nodes (confirmed by histopathology) and non-nodal tissues.
Based on these tables, values for true positive (TP), true negative (TN), false positive (FP), and false negative (FN) results were acquired. Diagnostic performance was then evaluated through the calculation of accuracy [TP+TN/TP+TN+FP+FN], sensitivity [TP/TP+FN], specificity [TN/TN+FP], and false negative rates [FN/FN+TP]. These values were analyzed and compared using a Chi-square analysis for statistically significant differences with a 95% confidence interval (p<0.05). The researchers also conducted subgroup analyses to compare the performance of the localization methods in two specific patient groups: those who received neoadjuvant therapy before surgery and those with a history of prior excision biopsy.
RESULTS
Demographics and Distribution
The researchers included a total of 350 female patients diagnosed with early-stage breast cancer in this study. They excluded data from 65 patients because of missing information. While this exclusion could have led to overestimating or underestimating calculated values, the researchers believe it will not significantly impact the analysis. The ages ranged from 28 to 88 years, with a
mean of 54.8 years. The majority (N = 270) were ≥ 45 years old, while the remainder (N = 80) were younger. The right breast (N = 180) was affected more frequently than the left (N =151), with a small proportion (N = 19) having bilateral involvement. A total of 17 patients had undergone neoadjuvant chemotherapy, and 97 patients had previous surgical excision before SLN localization (Table 1).
TABLE 1 Sociodemographic profile (n =350).
Characteristics
n
Frequency
Age
< 45 years old
80
22.9 %
≥ 45 years old
270
77.1 %
Laterality
Right
180
51.4 %
Left
151
43.1 %
Bilateral
19
5.5 %
Neoadjuvant Therapy
None
333
95.1 %
Present
17
4.9 %
Previous Excision
None
253
72.3 %
Present
97
27.7 %
Histologic Type
Invasive Ductal Carcinoma
232
66.3 %
Ductal Carcinoma In-Situ
55
15.7 %
Invasive Lobular Carcinoma
12
3.4 %
Papillary, mucinous, tubulolobular, apocrine
51
14.6 %
Tumor Size
< 1 cm
56
16.0 %
≥ 1 cm
225
64.3 %
No residual carcinoma
67
19.7 %
Localization Method
Blue Dye Only
167
47.7 %
Blue Dye + Lymphoscintigraphy
183
52.3 %
TABLE 2 Tissue counts by localization method.
Localization Method
Color
SLN
Non-Nodal
All patients
Blue Dye (n=552)
Blue
434
17
Not Blue
92
9
Blue Dye with Lymphoscintigraphy (n=577)
Hot and/or Blue
542
12
Not Hot, Not Blue
17
6
Patients with Neoadjuvant Chemotherapy
Blue Dye (n=17)
Blue
12
0
Not Blue
5
0
Blue Dye with Lymphoscintigraphy (n=23)
Hot and/or Blue
23
0
Not Hot, Not Blue
0
0
Patients with Previous Excision
Blue Dye (n=147)
Blue
111
1
Not Blue
33
2
Blue Dye with Lymphoscintigraphy (n=174)
Hot and/or Blue
165
5
Not Hot, Not Blue
2
2
Overall Performance of Localization Techniques
Five hundred fifty-two tissues were localized using blue dye alone, and 577 tissues were submitted for analysis following combined blue dye and lymphoscintigraphy (Table 2). For blue dye alone, the sensitivity was 82.5%, specificity was 34.6%, false negative rate was 17.5%, and diagnostic accuracy was 80.3%. Compared to blue dye alone, the combined method significantly improved the sensitivity (97.0%, p<0.001), reduced the false negative rate (3.0%, p<0.001), and increased the diagnostic accuracy (96.0%, p<0.001). However, the specificity remained comparable (33.3%) between the two methods (Table 3).
TABLE 3 Diagnostic performance of localization methods in all patients.
Dye Only
Dye with Lymphoscintigraphy
Chi-square Value
p-value
Sensitivity
82.5 %
97.0 %
62.6
<0.0001a
Specificity
34.6 %
33.3 %
0.008
0.93
False Negative Rate
17.5 %
3.0 %
62.6
<0.0001a
Diagnostic Accuracy
80.3 %
95.0 %
57.0
<0.0001a
a = Significant at p<0.001
Performance in Subgroups
In patients with neoadjuvant chemotherapy (N = 17), the combined method achieved 100% sensitivity, specificity, and accuracy, with a 0% false negative rate, compared to 70.6% accuracy and 70.6% sensitivity with blue dye alone (Table 4). However, due to the small sample size in this subgroup, statistical comparisons were not possible.
TABLE 4 Diagnostic performance of localization methods in patients with neoadjuvant chemotherapy.
Dye Only
Dye with Lymphoscintigraphy
Chi-square Value
p-value
Sensitivity
70.6 %
100 %
N/Aa
N/Aa
Specificity
N/Aa
100 %
False Negative Rate
29.4 %
0.0 %
Diagnostic Accuracy
70.6 %
100 %
a= Cannot be computed
Patients who underwent previous excision biopsy (N = 97) performed significantly better with the combined method than blue dye alone. The combined method achieved a sensitivity of 98.8% and an accuracy of 96.0%, while blue dye alone had a sensitivity of 77.1% and an accuracy of 76.9% (p<0.0001). Additionally, the combined method significantly reduced the false negative rate (1.2%) compared to blue dye alone (22.9%, p<0.0001). Specificity remained comparable between the groups (Table 5).
TABLE 5 Diagnostic performance of localization methods in all patients with previous excisions.
Dye Only
Dye with Lymphoscintigraphy
Chi-square Value
p-value
Sensitivity
77.1 %
98.8 %
36.5
<0.0001a
Specificity
66.7 %
28.6 %
1.3
0.26
False Negative Rate
22.9 %
1.2 %
36.5
<0.0001a
Diagnostic Accuracy
76.9 %
96.0 %
26.1
<0.0001a
a= Significant at p<0.001
DISCUSSION
The combined blue dye and lymphoscintigraphy method demonstrated significantly higher sensitivity, lower false negative rate, and comparable specificity compared to blue dye alone for SLN localization overall (p<0.001). In patients with previous excision, the combined method showed superiority with significantly higher sensitivity, accuracy, and lower false negative rate than blue dye alone (p<0.001). For patients receiving neoadjuvant therapy, the combined method achieved 100% accuracy and no false negatives, while blue dye alone showed lower accuracy (70.6%) and a higher false negative rate (29.4%). However, the small sample size in this subgroup limits definitive conclusions.
For the blue dye group in the current study, detection accuracy and specificity values were lower than previously reported in the literature, with an 80.3% detection rate and 34.6% specificity as opposed to the expected values of 95-98% and 95%, respectively.3-5 However, the calculated sensitivity of 82.5% and false negative rate of 17.5% seem almost to parallel the 87% sensitivity and 13% false negative rates reported by Li et al.18 On the other hand, the combination technique yielded a higher sensitivity of 97% than the expected 83.3%, and a detection rate of 95% that is comparable to the 98% detection rate in reported previous literature.8-9,13 The false negative rate of
3.0% in this study is lower than the 4.34% reported by Pesek et al. and is within the recommended false negative rate of less than 5.0% by the American Society of Breast Surgeons.12,18
While both localization techniques demonstrate adequate detection accuracy and sensitivity for SLN detection, as shown by values in this study and previous literature, the combination of dye and radiotracer is more advantageous in higher detection rate and sensitivity and significantly lower false negative rates. This coincides with findings from previous meta-analyses regarding the significantly greater detection accuracy and lower false negative rates of the combination technique.10-12 In our research, however, this technique also showed greater sensitivity than the dye-only method (95% vs 80%). This finding differs from previous literature, reporting no significant difference between the two.10-14 Meanwhile, the specificity of both techniques was comparable and consistent with previous findings by Gupta et al.13
The results of the subgroup analysis demonstrate a particular advantage of using blue dye and lymphoscintigraphy for patients who underwent prior excision biopsy or surgery before SLN localization. This study reveals a novel finding not previously reported in the existing literature. For the neoadjuvant therapy subgroup, results from the combination technique may be comparable with findings by Tee et al., who found a 78-93% identification rate and a 30-40% false negative rate when using blue dye to localize sentinel nodes in these patients (70.6% and 29.4% in the current study, respectively).15 Our study yielded a much higher accuracy of 100% and no false negative cases, although the small sample size for this sub-analysis may still limit the interpretation of these values. Regarding neoadjuvant chemotherapy, the more effective localization method remains a topic for further investigation.
The nature of the combination procedure may explain these findings. This technique utilizes two localization agents (blue dye and radiotracer) instead of just one. This approach increases the number of tissues identified, including those positive for both agents (blue dye and radiotracer positive), those positive only for blue dye (blue dye positive only), and those positive only for the radiotracer (radiotracer positive only). This comprehensive identification leads to a higher true positive rate, as evidenced by the significantly improved sensitivity and detection accuracy for sentinel lymph nodes (SLNs). Additionally, it reduces the number of false negative results. The study also highlights a noteworthy finding: the specificity of both techniques was significantly lower than values reported in previous literature. This discrepancy might be explained by the limited number of non-nodal tissues excised by the surgeons during the procedures. Their experience and skill likely influenced this decision (26 tissues for blue dye; 18 tissues for combination). A larger sample size of non-nodal tissues could improve the specificity of the results. This small number of non-SLN samples tends to underestimate the specificity of both methods.
Data gathered in this study are subject to some limitations. Currently, no standardized methods or thresholds consider tissues blue-stained or radiotracer positive. As such, subjective interpretation of slight staining and minimal tissue counts may significantly alter the yield of sentinel nodes. Convenience sampling and small sample sizes in subgroup analyses that do not meet the minimum required to achieve power may also limit generalizability to the broader population. Lastly, the retrospective design limits establishing causality between localization methods and outcomes.
Considering the significant advantages and limitations, the combined method shows promise as the preferred technique for SLN localization in most patients, including those with previous breast excision. Further research is needed to investigate the combined method’s efficacy in more extensive, diverse populations and with standardized protocols to strengthen these findings and address limitations.
However, it is crucial to acknowledge the limitations of this study, including convenience sampling and small subgroup sizes, which limit the generalizability of findings to the broader population. The need for standardized protocols for blue dye interpretation and gamma probe count thresholds warrants further investigation. The study underscores the need for further research to solidify these findings. First, conducting similar studies with more extensive and diverse patient populations would strengthen the generalizability of the results. Second, implementing standardized protocols across studies would ensure consistency and allow for more robust data comparison. Finally, researchers should specifically investigate the efficacy of the combined localization method in patients who received neoadjuvant chemotherapy before surgery. This targeted investigation would provide valuable insights into the technique’s performance in this patient group.
CONCLUSION
This study compared the diagnostic performance of blue dye alone and combined blue dye with lymphoscintigraphy for sentinel lymph node (SLN) localization in breast cancer patients. The results demonstrated that the combined method significantly improved the localization of true lymph node tissue (sensitivity) and the non-identification of non-nodal tissue (diagnostic accuracy), as well as reduced the risk of missing nodal tissues (false negative rate). These findings were particularly evident in patients who had undergone previous excision of the affected breast tissue.
Based on these results, the combined method of blue dye and lymphoscintigraphy shows promise as a potentially preferred technique for SLN localization in most patients undergoing surgery for early-stage breast cancer, especially those with prior excision. This approach can potentially improve the accuracy of surgical procedures and patient outcomes. Although cautious interpretation and further research are still necessary, the current study suggests that the combined blue dye and lymphoscintigraphy method offers potential advantages for SLN localization compared to blue dye alone.
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DATA AVAILABILITY STATEMENTS
The authors can make the gathered data underpinning this article’s conclusions accessible upon request without unnecessary restriction. The authors cannot publicly share the
data to protect ethical considerations and participant privacy. However, they can make it available upon reasonable request with approval from the institutional ethics committee.
ETHICS STATEMENT
The Ethics Review Board/Committee of The Medical City Ortigas approved the
study. The researchers conducted the study using local legislation and institutional requirements. The Ethics Committee/Institutional Review Board waived the provision of written informed consent for the retrospective analysis of de-identified patient data.
AUTHORS CONTRIBUTION
LRM, conceptualization, literature review, protocol writing and editing; data collection, data analysis, manuscript writing, and editing; EL, conceptualization, protocol review and editing, manuscript review and editing; NPH, conceptualization, protocol review and editing, supervision
FUNDING
This research received no external funding.
CONFLICT OF INTEREST
The authors declare no conflicts of interest related to commercial or financial relationships.
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