Original Research
Frontiers in Cancer Control and Society ·
Volume 4 - 2026 | https://doi.org/10.3389/fcacs.2026.1844383
Childhood cancer incidence, survival and mortality patterns in Argentina, 2000–2022: from the Argentine Oncopediatric Registry (ROHA)
- Florencia Moreno1*corresponding author
- Maria Agustina Chaplin1
- Mariana Nana1
- María Graciela Abriata1
- Argentine Oncopediatric Registry, National Cancer Directorate, Ministry of Health, Buenos Aires, Argentina
Abstract
Population-based cancer registries are essential tools for monitoring the burden of childhood cancer and guiding evidence-based public health policies. In pediatric oncology, long-term registry data are particularly valuable for evaluating survival trends, identifying inequities, and informing health system strengthening. The Argentina Oncopediatric Registry (ROHA), established in 2000, provides a unique framework for evaluating long-term trends in childhood cancer incidence, survival, and mortality. We analyzed population-based data from ROHA for children aged 0–14 years diagnosed with cancer(2000-2022).Incidence was calculated using age-standardized rates (ASR). Overall survival(OS) was estimated using standard survival analysis techniques and evaluated by calendar period, tumor group, geographic region, and Human Development Index (HDI). National mortality data were obtained from the National Statistical Office. Adolescents aged 15–19 years were excluded due to incomplete registry coverage. During the study period, 31,241 childhood cancer cases were registered, corresponding to an incidence ASR of 131 cases/million children per year, which remained stable over time. Five-year OS improved substantially, increasing from 59.7% in 2000–2004 to approximately 70% in the most recent period. The largest survival gains were observed for leukemias and central nervous system tumors. However, improvements slowed in recent years, and marked disparities persist by tumor type, geographic region, and Human Development Index level. The national age-standardized childhood cancer mortality rate per 100,000 children was 3.73 in 2021–2022 and showed a declining trend over the study period, consistent with improvements in overall survival. Over the past 25 years, Argentina has achieved meaningful progress in childhood cancer survival while maintaining stable incidence rates. Argentina's survival estimates are among the highest reported in Latin America; however, important regional and socioeconomic disparities persist. Integrating high-quality registry data with national cancer policies, social protection mechanisms, and strategies to strengthen clinical support—through the Childhood and Adolescent Cancer Protection Law and the Unique Pediatric Oncology Certificate—offers a model to improve equity, quality of care, and outcomes in Argentina and similar middle-income settings.
Keywords
Background
Population-Based Cancer Registries (PBCRs) are fundamental tools for designing and implementing evidence-based public health policies. They provide essential data on cancer incidence, distribution, survival, and temporal trends, supporting health system planning, resource allocation, and performance evaluation. Hospital-Based Cancer Registries (HBCRs) complement PBCRs by contributing detailed clinical information relevant to patient care and service organization (1–4). Childhood cancer represents one of the leading causes of disease-related mortality among children and adolescents worldwide, despite being a relatively rare group of diseases. Its epidemiology differs substantially from adult cancer, with a predominance of embryonal and hematologic malignancies and unique biological and developmental characteristics. Population-based cancer registries play a critical role in monitoring incidence, survival, and temporal trends (5–7). However, in upper-middle-income countries, childhood cancer surveillance may face challenges related to fragmented health systems, heterogeneous access to specialized care, variable registry coverage, and limitations in long-term follow-up.
Survival in pediatric oncology is determined by a complex interplay of biological, clinical, and socioeconomic factors. Tumor biology and aggressiveness are key determinants, but outcomes are also strongly influenced by the timeliness of diagnosis, access to standardized treatment protocols, the training of professionals, and the availability of specialized pediatric oncology units and adequate supportive care. Organizational aspects—such as referral pathways, continuity of care, and access to essential medicines—further shape prognosis. In addition, social determinants, including socioeconomic status, parental education, and geographic distance to treatment centers, have been consistently associated with disparities in treatment completion and survival (1, 4, 8–10).
In Latin America, the development of childhood cancer registries has been heterogeneous. Countries such as Chile, Peru, Argentina, and Uruguay have established specific pediatric oncology registries to enable dedicated analyses. In addition, regional initiatives such as VIGICANCER (11) in Colombia and PACARSS in Mexico have contributed to strengthening pediatric cancer surveillance, while national systems such as RENCI (12) in Chile and the National Childhood Cancer Registry (RNCI) (13) in Uruguay provide more structured and comprehensive data sources. At the global level, the International Agency for Research on Cancer (IARC) has supported registry development through initiatives such as the International Incidence of Childhood Cancer (IICC), while large international survival studies, including CONCORD, have incorporated pediatric cancer data from the region. These initiatives have enabled standardized comparisons of incidence and survival across countries and over time. However, the sources contributing to these analyses remain methodologically heterogeneous, reflecting differences in data collection, coverage, and quality across countries (1, 4, 9, 10, 14).
In Argentina, the Argentine Oncopediatric Registry (ROHA) was established in 2000 and has been coordinated by the National Cancer Institute within the Ministry of Health since 2010. In 2016, the National Program for Childhood Cancer (PROCUINCA) was formally created through a ministerial resolution, incorporating ROHA as one of its core components for surveillance and monitoring. More recently, the National Childhood Cancer Law (2023) consolidated the principles and care strategies promoted by PROCUINCA. Under this new regulatory framework, the registry serves as the fundamental basis of the system's structure, ensuring data traceability, continuous evaluation of care processes, and evidence-based decision-making. Over 25 years of continuity, ROHA has registered more than 41,000 childhood cancer cases, achieving national coverage exceeding 90% among children under 15 years of age, as previously reported (15).
Adolescents aged 15–19 years were not included in the present analysis, as registry coverage for this age group was insufficient to ensure reliable incidence estimates. Since 2023, case reporting has been mandatory under the Childhood and Adolescent Cancer Protection Law (Law No. 27.674), which also introduced the Unique Pediatric Oncology Certificate (CUOP), linking registry data with access to health, economic and social benefits.
Although regional and international estimates of childhood cancer incidence and survival are available, few studies from Latin America have integrated long-term population-based analyses of incidence, survival, and mortality trends within a single national pediatric cancer registry framework. In Argentina, the availability of 25 years of high-coverage ROHA data provides a unique opportunity to evaluate temporal changes in outcomes, regional and socioeconomic disparities, and persistent challenges for pediatric cancer control.
This study aims to describe trends in incidence, survival, and mortality over 25 years of pediatric cancer registration in Argentina using ROHA data, and to discuss progress achieved, persistent challenges, and implications for national and regional health policy.
Methods
Country information
Argentina is commonly grouped into five major geographic regions, as shown in Figure 1: Central Region (CTR): Buenos Aires, Ciudad Autónoma de Buenos Aires, Córdoba, Entre Ríos, Santa Fe; Northwest Region (NWR): Catamarca, Jujuy, La Rioja, Salta, Santiago del Estero, Tucumán; Northeast Region (NHR): Chaco, Corrientes, Formosa, Misiones; Cuyo Region (RC): Mendoza, San Juan, San Luis; and Southern Region (SR): Chubut, La Pampa, Neuquén, Río Negro, Santa Cruz, Tierra del Fuego (Figure 1). These regions were used as analytical units to explore geographic variations in incidence, survival, and mortality.

Population distribution and socioeconomic conditions vary substantially across regions. The Central Region concentrates the largest share of the national and pediatric population and has the highest urbanization level, whereas the NWR and NHR have greater rural dispersion and less favorable socioeconomic indicators. Argentina is classified as a high Human Development Index (HDI) country; however, marked regional inequalities persist in income, poverty, and health indicators. In recent years, GDP per capita has been estimated at approximately USD 13,000–14,000, while infant mortality and poverty rates remain substantially higher in northern regions compared with the central area of the country (16).
Argentina also has a heterogeneous ethnic composition. According to census-based estimates, approximately 2%–3% of the population self-identifies as Indigenous, with greater representation in the Northwest and Northeast regions (17).
Health system context
Argentina has a fragmented health system composed of 3 sectors: the public health sector with universal coverage, the social security and the private one. Since the 1990s, health care organization and financing have been largely decentralized to the provincial level. Although access to health care is nominally universal, pediatric oncology care is delivered through the public sector predominantly, with substantial regional variability in access and offering of specialized services. Several provinces lack the capacity to provide comprehensive treatment for certain pediatric cancers and therefore refer patients to higher-complexity centers in other jurisdictions. However, it may also introduce potential differential ascertainment across regions, as case detection and registration can be influenced by access to specialized services, referral patterns, and local health system capacity. At the same time, the ROHA framework allows documentation of referral and counter-referral pathways across institutions, facilitating longitudinal follow-up and continuity of registration despite migration.
Pediatric oncology care
Approximately 80% of children with cancer use the public sector for diagnosis and treatment.
Pediatric oncology care in Argentina is delivered through a heterogeneous network of 31 Pediatric Oncology Units (POU) providing partial or complete treatment, including 18 provincial referral centers with varying levels of complexity. In addition, several health centers manage childhood cancer cases without having a formally established POU, contributing to variability in expertise and availability of services. Care is highly centralized, as three high-complexity pediatric hospitals (Level 3) in Buenos Aires manage nearly 50% of all cases, and the National Pediatric Hospital alone receives more than 500 new oncology patients annually. The NHR, NWR, and SR lack maximum-complexity for some tumors, limiting local access to specialized diagnostics and treatment. As a result, patient migration is a structural feature of the system, with approximately 48% of children migrating for partial or complete treatment, predominantly toward the national tertiary Level 3 centers (15).
Inter-provincial migration is also limited by administrative barriers, leading to fragmented care. In many cases, treatment is shared between local hospitals and referral oncology units, resulting in sequential management across institutions.
Within this fragmented care framework, parent organizations and philanthropic foundations play a prominent role in supporting children with cancer and their families, complementing public health services and working in alignment with national policies to facilitate access to care, treatment continuity, and psychosocial support.
Sources
ROHA gathers information from a wide range of sources, including: all public and private paediatric departments of haematology/oncology, pathology services, radiotherapy centers, and surgical groups, as well as regional PBCR and cooperative medical groups since 2000, ensuring comprehensive coverage. All data is publicly accessible. This information is shared through publications approximately every two years (18).
These sources report all new cases and update the vital status of existing cases on an annual basis.
Demographic and disease information is collected following the standards of the International Agency of Research on Cancer (IARC) and the International Association of Cancer Registries (IACR) (2, 19). The histology and topography of malignancies are coded according to the International Classification of Diseases for Oncology, 3rd edition (ICD-O-3) (14) and the International Classification of Childhood Cancer - ICCC (20). ROHA's integration with national data sources, including the National Institute of Statistics and Censuses (INDEC) (21), Direction of Statistics and Health Information (DEIS), and National Registry of Persons (RENAPER) has enabled comprehensive analyses of incidence, mortality, and survival, positioning it as both an epidemiological and policy tool. The proportion of Death Certificate Only (DCO) cases was 3% overall.
For this study, all tumours in patients aged 0–14 years diagnosed between 2000 and 2022 were extracted from ROHA's database.
ROHA's estimated national coverage is 93%. Coverage was estimated by comparing the number of cases registered in ROHA with expected incidence rates derived from the International Incidence of Childhood Cancer, third edition (IICC-3), using a reference rate of approximately 140 cases per million children under 15 years of age.
The quality of the registry, as assessed by conventional indicators (e.g., completeness, consistency, and proportion of microscopically verified cases), has been considered acceptable and relatively uniform across regions and over time (1, 2).
Case definition
Cases were identified from the ROHA database. A case was defined as a child younger than 15 years diagnosed between January 1, 2000, and December 31, 2022, who was resident in Argentina at the time of diagnosis.
Neoplasms were classified according to the International Classification of Childhood Cancer, third edition (ICCC-3). In children with multiple primary malignancies, only the first primary tumor was included in the analyses. The analysis included malignant neoplasms (ICD-O behavior code/3). In addition, non-malignant tumors of the central nervous system (behavior codes/0 and/1) were included, in accordance with international recommendations for childhood cancer registration. For the survival analysis, cases diagnosed between January 1, 2000, and December 31, 2019 were included. Survival estimates were calculated by diagnostic quinquennium (2000–2004, 2005–2009, 2010–2014, and 2015–2019), geographic region, and HDI-province categories.
Statistical-analysis
Categorical variables are presented as counts and percentages. Incidence, mortality, and survival estimates are presented with their corresponding 95% confidence intervals. Incidence and mortality rates were calculated using Epidat (version 3.1). Annual incidence ASR per million children younger than 15 years were calculated using the Segi world standard population (22), and the National Vital Statistics Reports of INDEC.
The average annual percent of change (AAPC) and its 95% Confident Interval were calculated through the Permutation Test using the “Joinpoint regression” program from the National Cancer Institute (NCI) of the United States, representing the ASRś percentage of increase or decrease in the period. The reported AAPCs correspond to the overall study period.
Mortality trends were analyzed for the period 1999–2022 using biannual data points. To improve the stability of annual mortality estimates, data from 1999 to 2000 were combined and treated as a single observation in the Joinpoint regression analysis. Subsequent years were analyzed according to the same biannual approach.
Following standard registry conventions, the incidence date was defined as the date of histological confirmation. For cases identified through DCO, the incidence date was defined as the date of death. Age groups (0–4, 5–9, and 10–14 years) were used for the calculation of age-standardized incidence rates according to the world standard population.
Survival curves and probability of survival at 60 months were estimated using the Kaplan–Meier method. All reported cases were considered in the survival analysis, including those identified from death certificates. Overall survival was estimated using the Kaplan–Meier method. Survival distributions across geographic regions and calendar periods were compared using log-rank tests and univariate Cox proportional hazards models. Five-year OS probabilities along with 95% confidence intervals (95% CI) are presented.
The following variables were considered: diagnostic group according to the ICCC (leukaemia, lymphoma, brain neoplasms, neuroblastoma, retinoblastoma, renal tumours, hepatic tumours, malignant bone tumours, soft-tissue sarcomas, germ-cell tumours, and carcinoma), Human Development Index (HDI) and geographic region.
The Human Development Index from the United Nations Development Programme (UNDP) was selected as an indicator of socioeconomic status.
HDI of each province was used as a socioeconomic indicator to compare survival rates by province in both periods. Specifically, the HDI provides information on the status of each province as related to the possibility of leading a long and healthy life (life expectancy and infant mortality from preventable causes), education (literacy rate and quality of education rate), and decent standard of living (total family income per capita, employment rate, and unemployment rate).
Provinces were categorized into three groups (high, medium, and low HDI) according to the 2006 and 2016 provincial HDI classifications derived from national reports. Cut-off points were defined using tertiles of the provincial HDI distribution at each time point, resulting in relatively narrow ranges between categories. Based on their HDI 2006, provinces were classified into three groups: high (above 0.817), medium (between 0.802 and 0.817), and low (below 0.802). And for HDI 2016, high: above 0.851, medium: between 0.845 and 0.850, and low: below 0.846.
The average HDI 2006 of the country was 0.821; nine provinces had a high HDI, six had a medium HDI, and eight had a low HDI. And for HDI 2016, the average of the country was 0.851; seven provinces had a high HDI, seven had a medium HDI, and nine had a low HDI.
As a consequence, the composition of provinces within each HDI category varied between 2006 and 2016, reflecting changes in relative socioeconomic positioning over time. Therefore, comparisons between periods should be interpreted as reflecting differences between groups defined at each time point rather than fixed sets of provinces.
For analytical purposes, Buenos Aires Province was analyzed separately due to its substantially larger population size and case volume compared with the other provinces. All analyses were conducted in STATA 14.
Ethics statement
ROHA is a national childhood cancer registry operating under the Ministry of Health of Argentina as part of the national cancer surveillance system. Data collection, linkage, and analysis are conducted in accordance with national public health regulations and applicable data protection legislation. The present study used de-identified routinely collected registry data for epidemiological surveillance and public health purposes. According to the national regulatory framework, specific institutional ethics committee approval and informed consent were not required.
Results
In Argentina, according to the ROHA database, between 2000 and 2022, 31,241 cases of malignant tumors were registered in children under 15 years of age, with an average of 1,350 cases per year. The cancer incidence ASR was 131.0/million/year for the period 2000–2022. While most common pediatric cancer diagnoses showed stable incidence rates [AAPC: 0.1%; 95% CI (−0.2; 0.4); p = 0.6], a significant decline was observed in lymphomas and kidney tumors. In contrast, significant increases were identified in CNS tumors, malignant bone tumors, and other epithelial neoplasms and melanomas. Neuroblastoma showed a non-significant declining trend (Table 1). Survival analysis showed a substantial improvement in five-year OS for all cancers combined, increasing from 59.7% (2000–2004) to 65.5% (2005–2009), 70.0% (2010–2014), and 70.9% (2015–2019) (log-rank test, p < 0.001). The greatest improvements were observed for leukemias, CNS tumors, and renal tumors. However, survival trends varied across diagnostic groups, with some tumors showing more modest changes, fluctuations, or plateauing survival estimates over time (Table 2). Notably, overall survival appeared to plateau between 2010 and 2014 and 2015–2019, with overlapping confidence intervals.
Table 1. Age-standardized incidence rates (ASR) and temporal trends (AAPC) of childhood cancers by international classification of childhood cancer (ICCC-3), Argentina, 2000–2022.
| Cancer group (ICCC-3) | N | ASR | 95% CI | AAPC | 95% CI |
|---|---|---|---|---|---|
| I. Leukemias, myeloproliferative diseases, and myelodysplastic diseases | 11,678 | 49.2 | 44.9–53.5 | 0.2 | −0.2; 0.6 |
| II. Lymphomas and reticuloendothelial neoplasms | 3,611 | 14.5 | 12.2–16.8 | −1.0 | −1.6; −0.4 |
| III. CNS and miscellaneous intracranial and intraspinal neoplasms | 6,093 | 25.3 | 22.3–28.4 | 0.7 | 0.3; 1.2 |
| IV. Neuroblastoma and other peripheral nervous cell tumors | 1,668 | 7.6 | 5.8–9.3 | −1.1 | −2.4; 0.3 |
| V. Retinoblastoma | 1,043 | 4.9 | 3.4–6.3 | −0.7 | −1.7; 0.4 |
| VI. Renal tumors | 1,380 | 6.2 | 4.6–7.8 | −1.1 | −1.9; −0.3 |
| VII. Hepatic tumors | 431 | 1.9 | 1.1–2.8 | 0.1 | −1.0; 1.2 |
| VIII. Malignant bone tumors | 1,584 | 6.0 | 4.6–7.4 | 1.1 | 0.3; 1.9 |
| IX. Soft tissue and other extraosseous sarcomas | 1,890 | 7.8 | 6.1–9.5 | 0.3 | −0.5; 1.0 |
| X. Germ cell tumors, trophoblastic tumors, and neoplasms of gonads | 1,070 | 4.4 | 3.1–5.6 | 0.4 | −0.8; 1.6 |
| XI. Other malignant epithelial neoplasms and malignant melanomas | 628 | 2.4 | 1.5–3.3 | 2.3 | 0.7; 3.9 |
| XII. Other and unspecified malignant neoplasms | 165 | 0.7 | 0.2–1.2 | - | - |
| All cancers | 31,241 | 131.0 | 124.0–138.0 | 0.1 | −0.2; 0.4 |
AAPC was not estimated for ICCC group XII because the small number of cases precluded reliable trend analysis.
The age-standardized incidence rates (ASR) and the average annual percent change (AAPC) for all cancers are presented in bold.
Table 2. Five-year overall survival behavior according international classification of childhood cancer (ICCC-3) in children, 200–04, 2005–09, 2010–14 and 2015–19 .
| Cancer group (ICCC-3) | Periods | N | Deaths | OS (%) | 95% CI |
|---|---|---|---|---|---|
| I. Leukemias, myeloproliferative diseases, and myelodysplastic diseases | 2000–04 | 2,396 | 1,070 | 59.1 | 57.1–61.0 |
| 2005–09 | 2,357 | 887 | 65.9 | 64.0–67.8 | |
| 2010–14 | 2,668 | 871 | 69.7 | 67.9–71.4 | |
| 2015–19 | 2,724 | 803 | 71.8 | 70.1–73.4 | |
| II. Lymphomas and reticuloendothelial neoplasms | 2000–04 | 840 | 229 | 76.7 | 73.7–79.4 |
| 2005–09 | 794 | 227 | 75.4 | 72.3–78.3 | |
| 2010–14 | 721 | 142 | 82.5 | 79.6–85.1 | |
| 2015–19 | 808 | 117 | 86.4 | 83.8–88.5 | |
| III. CNS and miscellaneous intracranial and intraspinal neoplasms | 2000–04 | 1,183 | 733 | 45.3 | 42.5–48.1 |
| 2005–09 | 1,205 | 628 | 53.9 | 51.1–54.7 | |
| 2010–14 | 1,392 | 629 | 60.1 | 57.4–62.6 | |
| 2015–19 | 1,470 | 588 | 62.1 | 59.5–64.5 | |
| IV. Neuroblastoma and other peripheral nervous cell tumors | 2000–04 | 336 | 168 | 54.2 | 48.7–59.3 |
| 2005–09 | 398 | 178 | 58.3 | 53.3–63.0 | |
| 2010–14 | 401 | 157 | 62.8 | 57.9–67.4 | |
| 2015–19 | 374 | 160 | 58.8 | 53.6–63.6 | |
| V. Retinoblastoma | 2000–04 | 206 | 30 | 86.9 | 81.5–90.8 |
| 2005–09 | 249 | 29 | 90.8 | 86.4–93.8 | |
| 2010–14 | 244 | 23 | 91.8 | 87.6–94.6 | |
| 2015–19 | 223 | 13 | 94.1 | 90.1–96.6 | |
| VI. Renal tumors | 2000–04 | 308 | 97 | 71.8 | 66.4–76.4 |
| 2005–09 | 314 | 67 | 80.9 | 76.1–84.8 | |
| 2010–14 | 300 | 62 | 82.7 | 77.9–86.5 | |
| 2015–19 | 312 | 51 | 84.6 | 80.1–88.2 | |
| VII. Hepatic tumors | 2000–04 | 92 | 47 | 54.4 | 43.7–63.9 |
| 2005–09 | 86 | 42 | 54.7 | 43.6–64.5 | |
| 2010–14 | 98 | 47 | 54.1 | 43.7–63.3 | |
| 2015–19 | 96 | 33 | 66.7 | 56.3–75.1 | |
| VIII. Malignant bone tumors | 2000–04 | 310 | 181 | 46.5 | 40.8–51.9 |
| 2005–09 | 312 | 185 | 46.5 | 40.9–51.9 | |
| 2010–14 | 366 | 190 | 53.6 | 48.3–58.5 | |
| 2015–19 | 354 | 179 | 51.1 | 45.8–56.2 | |
| IX. Soft tissue and other extraosseous sarcomas | 2000–04 | 377 | 212 | 48.3 | 43.2–53.2 |
| 2005–09 | 386 | 174 | 59.1 | 54.0–63.8 | |
| 2010–14 | 442 | 170 | 64.7 | 60.1–69.0 | |
| 2015–19 | 449 | 185 | 60.5 | 55.8–64.9 | |
| X. Germ cell tumors, trophoblastic tumors, and neoplasms of gonads | 2000–04 | 185 | 44 | 81.1 | 74.7–86.0 |
| 2005–09 | 243 | 41 | 85.6 | 80.5–89.4 | |
| 2010–14 | 267 | 37 | 87.6 | 83.1–91.1 | |
| 2015–19 | 242 | 30 | 88.0 | 83.2–91.5 | |
| XI. Other malignant epithelial neoplasms and malignant melanomas | 2000–04 | 107 | 35 | 72.0 | 62.4–79.5 |
| 2005–09 | 110 | 20 | 82.7 | 74.3–88.6 | |
| 2010–14 | 152 | 23 | 84.9 | 78.1–89.7 | |
| 2015–19 | 161 | 25 | 85.6 | 79.1–90.2 | |
| XII. Other and unspecified malignant neoplasms | 2000–04 | 26 | 9 | 69.2 | 47.8–83.3 |
| 2005–09 | 52 | 28 | 48.1 | 34.1–60.8 | |
| 2010–14 | 36 | 13 | 66.7 | 48.8–79.5 | |
| 2015–19 | 32 | 13 | 59.4 | 40.5–74.0 | |
| All cancers | 2000–04 | 6,366 | 2,855 | 59.7 | 58.4–60.9 |
| 2005–09 | 6,506 | 2,506 | 65.5 | 64.3–66.6 | |
| 2010–14 | 7,087 | 2,364 | 69.7 | 68.6–70.7 | |
| 2015–19 | 7,245 | 2,197 | 70.9 | 69.8–71.9 |
Bold values indicate the five-year overall survival estimate for the most recent period (2015–2019).
Survival rates by regions are shown in Table 3. The Central and Southern regions had the highest estimated five-year OS, 72.0% (95% CI: 71.0–72.9) and 71.9% (95% CI: 68.9–74.7), respectively, while the NWR had the lowest OS, 63.3% (95% CI: 61.0–65.5).
Table 3. Distribution of cases, deaths and five-year overall survival by region. 2010–2019 .
| Regions | Cases | Deaths | Five-year OS | Log rank test | ||
|---|---|---|---|---|---|---|
| n | n | % | 95% CI | |||
| Central region (CTR) | 9,105 | 2,746 | 72.0 | 71.0–72.9 | <0.01 | |
| Northwest region (NWR) | 1,723 | 665 | 63.3 | 61.0–65.5 | ||
| Northeast region (NHR) | 1,555 | 537 | 67.9 | 65.5–70.2 | ||
| Region of Cuyo (CR) | 1,034 | 333 | 69.1 | 66.2–71.9 | ||
| South region (SR) | 915 | 274 | 71.9 | 68.9–74.7 | ||
| Argentina | 14,332 | 4,561 | 70.3 | 69.5–71.0 |
The five-year OS between 2000 and 2009 and 2010–2019 for low-HDI provinces improved from 57.4% to 68.1%. For medium-HDI, it increased from 58.1% to 68.9%, and for high-HDI provinces, from 64.2% to 73.1% (Table 4).
Table 4. Five-year overall survival according HDI-provinces, periods 2000–2009 and 2010–2019.
| Categories by HDI provinces | 2000–2009(2006 HDI classification) | 2010–2019(2016 HDI classification) | ||||||
|---|---|---|---|---|---|---|---|---|
| n | Five-year OS | 95% CI | Log ranktest | n | Five-year OS | 95% CI | Log ranktest | |
| Low | 2,647 | 57.4 | 55.5–59.3 | <0.01 | 4,212 | 68.1 | 66.6–69.5 | <0.01 |
| Medium | 1,453 | 58.1 | 55.5–60.6 | 2,884 | 68.9 | 67.2–70.6 | ||
| High | 4,076 | 64.2 | 62.7–65.6 | 1,714 | 73.1 | 71.0–75.2 | ||
| Buenos Aires | 4,696 | 65.5 | 64.2–66.9 | 5,522 | 71.8 | 70.5–72.9 |
The age-standardized mortality rate (AMR) decreased from 4.56 per 100,000 under 15 years of age in 1999–2000 to 3.73 in 2021–2022. The mortality trend showed a significant decline, with an Annual Percentage Change (APC) of −1.9% (CI95%: −2.8 to −1.1) from 1999 to 2022, consistent with the observed improvements in overall survival. The analysis was performed using Joinpoint regression accepting the best model given by default by the program among other models tested with two joinpoints (Figure 2).

The age-standardized mortality rate (AMR) decreased from 4.56 per 100,000 under 15 years of age in 1999–2000 to 3.73 in 2021–2022. The mortality trend showed a significant decline, with an Annual Percentage Change (APC) of −1.9% (95% CI: −2.8 to −1.0) from 1999 to 2022, consistent with the observed improvements in overall survival. The analysis was performed using Joinpoint regression accepting the best model given by default by the program among other models tested with two joinpoints (Figure 2).
Discussion
Incidence trends
Over the past 25 years, childhood cancer incidence in Argentina has remained relatively stable, with an ASR of approximately 131 cases per million children per year. This estimate is consistent with reports from population-based registries in Latin America (1, 2) and remains lower than rates observed in many high-income countries, where increasing incidence trends have been described (1, 4, 9, 19, 23–26). In these settings, part of the increase has been attributed to improved diagnostic capacity, enhanced case ascertainment, and changes in classification systems rather than a true rise in disease occurrence (23, 27).
Although overall incidence remained stable, significant increases were observed for CNS tumors, malignant bone tumors, and malignant epithelial neoplasms and melanomas. Similar trends, particularly for epithelial neoplasms such as thyroid carcinoma, have been described internationally and may partly reflect increased diagnostic intensity, improved imaging availability, and evolving pathological classification (23, 24). Increases in CNS tumor incidence may also be influenced by broader access to neuroimaging and improved diagnostic capabilities over time.
Long-term incidence stability in the country may reflect the maturity and relatively high completeness of the ROHA system and sustained national case capture. However, persistent regional differences in diagnostic capacity and access to specialized services suggest that some degree of differential ascertainment may still exist, and incidence stability should therefore be interpreted cautiously. Continued investment in high-quality registration, including linkage with mortality, hospital-based cancer registries (HBCR), and administrative databases, is essential to ensure accurate interpretation of trends. The modest decline observed for lymphomas and renal tumors should also be interpreted cautiously, as international evidence shows heterogeneous patterns, suggesting that national or regional factors may contribute to these findings (19, 28).
Survival trends in an international context
Although childhood cancer survival in Argentina has improved substantially over the past two decades, five-year OS remains around 70% in the most recent period, below levels reported in highincome countries, where survival exceeds 80%–85% (3, 4, 25, 26). However, Argentina's survival estimates are comparable to those reported for several Latin American countries participating in CONCORD-4, including Brazil and Mexico, and remain higher than those observed in other countries in the region. At the same time, survival remains below that reported in Chile and Uruguay, highlighting persistent inequalities in pediatric cancer outcomes across Latin America (29). The most pronounced gains were observed for leukemias and central nervous system tumors, reflecting advances in diagnosis, risk stratification, treatment protocols, and supportive care. Survival for lymphomas and traditionally high-survival tumors such as retinoblastoma approaches levels reported in other regional middle-income settings. However, survival improvements appear to have slowed during the last two quinquennia. Several tumor groups—including neuroblastoma, malignant bone tumors, soft tissue sarcomas, and some CNS tumors—showed limited or inconsistent gains. This plateau mirrors international experience, suggesting that further progress increasingly depends on equitable access to high-complexity diagnostics, precision therapies, multidisciplinary expertise, and robust health system infrastructure (4, 30–33).
Global and regional initiatives led jointly by SIOP, SLAOP, WHO, and partnerships with institutions such as St. Jude Children's Research Hospital have been instrumental in supporting capacity building and network strengthening in Latin America. Through the WHO Global Initiative for Childhood Cancer, these efforts aim to reduce survival gaps and promote sustainable improvements in childhood cancer outcomes (10, 34, 35). Argentina has already surpassed the WHO Global Initiative target of 60% five-year overall survival, reaching 70.9% in the most recent period.
Over the past two decades, Argentina has achieved substantial improvements in childhood cancer survival, with five-year overall survival increasing from 59.7% to 70.9%. Current survival estimates are among the highest reported in Latin America in population-based studies and exceed those observed in several middle-income countries in the region. However, important internal disparities persist. The survival gap between the CTR and NWR approaches the differences observed between some middle-income and high-income settings, highlighting how national averages may conceal major inequities in access and outcomes within the country. The trajectory of survival improvement observed in Argentina also resembles the historical progression described in high-income countries during earlier phases of pediatric oncology system development, suggesting that continued investment in specialized care networks, supportive care, and equitable access may yield further gains.
Regional and socioeconomic disparities
Despite overall survival gains, marked geographic and socioeconomic disparities persist in Argentina. Survival remains highest in the CTR, where high-complexity pediatric oncology services are concentrated, and lowest in the NWR and NHR. These geographic differences are consistent with underlying socioeconomic gradients, with lower survival consistently observed in provinces with lower Human Development Index (HDI), although the gap has narrowed over time.
Although this study was not designed to directly evaluate the mechanisms underlying regional survival differences, these disparities may be influenced by unequal access to specialized diagnosis and treatment, transportation barriers, referral pathways, and variability in supportive care infrastructure across regions. Inter-provincial migration for cancer care is also a structural feature of the Argentine pediatric oncology system, frequently involving shared-care arrangements and referrals of high-risk patients to national high-complexity centers, which may further contribute to fragmented care and complicate interpretation of regional outcome differences. National initiatives—including early diagnosis programs, standardized clinical guidelines, categorization of oncology units, and expanded nursing education—have been implemented to address these inequities and are now embedded within the Childhood and Adolescent Cancer Protection Law.
These regional disparities must also be interpreted within the context of Argentina's fragmented health system, where pediatric oncology care is frequently distributed across multiple jurisdictions and providers. Although the Argentine health system is characterized by multiple funders and providers, childhood cancer care is largely concentrated in specialized referral centers participating in the ROHA network. This organizational structure has facilitated nationwide case ascertainment and contributed to the high coverage achieved by the registry despite underlying inequalities in access and health system fragmentation. Nevertheless, maintaining comprehensive and timely case registration requires sustained coordination across institutions, jurisdictions, and health subsystems, particularly in the context of shared-care arrangements, inter-provincial referrals, and administrative barriers that may affect continuity of care and data completeness. Shared-care arrangements, administrative barriers between health subsystems, and uneven availability of specialized services may affect continuity of care, timely referral, access to supportive care resources, and the completeness and timeliness of case registration across jurisdictions.
Administrative constraints and limitations in terrestrial and aerial transport may also affect timely access to referral centers, often requiring long-distance migration for treatment and contributing to fragmented care. Parent organizations and foundations play an important complementary role by supporting accommodation, transportation, medication access, and psychosocial care, particularly for families who must migrate for treatment. While this collaboration enhances system resilience, it also underscores the need to further strengthen public-sector capacity to ensure equitable access independent of local external resources.
A distinctive feature of the Argentine model is the recent integration of cancer surveillance with social protection. Through linkage of ROHA data to the Unique Pediatric Oncology Certificate (CUOP), registry-based surveillance has the potential to support access to health and social benefits and preserve diagnostic information electronically for long-term continuity of care, reinforcing a patient-centered, rights-based approach. This integration may also facilitate administrative processes related to treatment coverage, transportation support, and continuity of care for children with cancer and their families. In this context, cancer surveillance extends beyond epidemiological monitoring and becomes part of a broader social protection strategy within pediatric oncology care.
Although the implementation and impact of CUOP and Law 27.674 have not yet been formally evaluated, their integration within the national pediatric oncology framework represents an important area for future policy and health services research. Although inter-provincial migration is a structural feature of pediatric oncology care in Argentina, migration-stratified survival analyses were beyond the scope of the present study. Interpretation of migration effects is complex because care is frequently shared across institutions and many high-risk patients are preferentially referred to high-complexity national centers, introducing potential referral and severity biases. Future multicenter and longitudinal analyses incorporating clinical, social, and health-system variables may help better characterize disparities in outcomes and guide equity-oriented pediatric oncology policies in Argentina.
The survival plateau in the most recent quinquennium
The apparent plateau in overall survival during the most recent quinquennium likely reflects the increasing difficulty of achieving additional gains once survival for more curable malignancies has improved substantially. In Argentina, persistent challenges remain concentrated in tumors requiring highly specialized multidisciplinary management, including neuroblastoma, malignant bone tumors, hepatic tumors, soft tissue sarcomas, and some CNS tumors. These neoplasms often depend on timely access to molecular diagnostics, complex surgery, radiotherapy, intensive supportive care, and coordinated referral networks, resources that remain unevenly distributed across the country.
Limitations in clinical supportive care—including pediatric intensive care availability, management of severe infectious complications, specialized nursing, transfusion support, and rehabilitation services—continue to represent major challenges in some regions. In addition, treatment-related infectious complications remain an important cause of mortality, particularly among children with leukemia. Although national referral pathways have expanded over time, many patients continue to require inter-provincial migration for partial or complete treatment, which may contribute to delays, fragmented care, and difficulties in treatment continuity. These findings suggest that future survival gains in Argentina will require not only maintaining equitable access to treatment, but also strengthening integrated high-complexity pediatric oncology care and supportive care capacity across regions.
Limitations
This study has some limitations. First, survival estimates represent observed overall survival rather than net survival; therefore, comparisons with studies reporting net survival should be interpreted with caution. However, in childhood cancer, non-cancer mortality is expected to be low. Second, although vital status was updated through linkage with the national mortality database, residual loss to follow-up or informative censoring cannot be completely excluded. Third, regional and HDIbased comparisons were unadjusted and should be interpreted as descriptive rather than causal. In addition, HDI was measured at the provincial level and may not reflect individual socioeconomic conditions, creating the possibility of ecological inference. Fourth, differential ascertainment across regions may persist because access to specialized diagnostic and treatment services varies within the country. Fifth, mortality data were analyzed only at the national level, limiting the evaluation of subnational mortality disparities. Sixth, treatment abandonment, a major contributor to childhood cancer mortality in many low- and middle-income countries, was not systematically captured in ROHA and could therefore not be evaluated in this study. Historically, treatment abandonment has not been considered a predominant challenge within the Argentine pediatric oncology system, although future studies incorporating standardized measures of treatment continuity would be valuable. Finally, this study was restricted to children aged 0–14 years. Adolescents aged 15–19 years were not included because their care pathways in Argentina are more heterogeneous and often distributed across pediatric and adult oncology services, which may affect registration completeness and comparability. Therefore, findings should not be extrapolated to the adolescent and young adult population.
Conclusions
Twenty-five years of population-based data from ROHA document substantial progress in childhood cancer survival in Argentina alongside stable incidence rates. Despite these advances, survival remains below levels observed in high-income countries, and important regional and socioeconomic disparities persist.
Future priorities should include strengthening pediatric oncology capacity in underserved regions, reducing administrative and geographic barriers to referral and treatment, and expanding equitable access to high-complexity diagnostics and novel therapies. Argentina's integration of registry-based surveillance with national pediatric cancer policies provides a relevant model for advancing equityoriented childhood cancer control in middle-income settings.
Generative AI statement
The author(s) declared that generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
Footnotes
Edited by: Vesna Zadnik, Institute of Oncology Ljubljana, Slovenia
Reviewed by: Dalia Ramírez-Ramírez, Biomedical Research Center of East (CIBIOR), Mexico
Oscar Ramirez, Clínica Imbanaco, Colombia
Statements
- Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
- Funding
The author(s) declared that financial support was not received for this work and/or its publication.
- Data availability
The original contributions presented in the study are included in the article/Supplementary Material, further inquiries can be directed to the corresponding author.
- Author contributions
FM: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Writing – original draft, Writing – review & editing. MC: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Writing – original draft, Writing – review & editing. MN: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Writing – original draft, Writing – review & editing. MA: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Project administration, Software, Supervision, Writing – original draft, Writing – review & editing.
- Acknowledgements
The authors would like to thank Guillermo Chantada for their constructive comments and are particularly grateful to the PROCUINCA team for their dedicated assistance.
References
- 1. Steliarova-Foucher E, Colombet M, Ries LAG, Moreno F, Dolya A, Bray F. International incidence of childhood cancer, 2001–10: a population-based registry study. Lancet Oncol. (2017) 18 (6): 719 – 31. doi:10.1016/S1470-2045(17)30186-9
- 2. Dos Santos Silva I. International Agency for Research on Cancer. In: Cancer Epidemiology: Principles and Methods. Lyon: IARC (1999).
- 3. Kaatsch P. German Childhood Cancer Registry Annual Report 2022. Göttingen: GCCR (2022)
- 4. Allemani C, Carlo D, Ssenyonga V. (CONCORD-4): a cancer survival Index derived for 68 countries by analysis of individual records for 613 021 children from 307 population-based cancer registries the lancet. 1990–2019 (CONCORD-4): a cancer survival Index derived for 68 countries by analysis of individual records for 613 021 children from 307 population-based cancer registries. Lancet. (1990) 407: 1335 – 59. doi:10.1016/S0140-6736(26)00189-3
- 5. Shiels MS, Haque AT, Jones RR, Kitahara CM, Glod JW, Widemann BC. Trends in childhood and adolescent cancer incidence rates in the United States between 2001 and 2022. Cancer Discov. (2026) 16 (4): 686 – 96. doi:10.1158/2159-8290.CD-25-1493
- 6. Siegel RL, Kratzer TB, Wagle NS, Sung H, Jemal A. Cancer statistics, 2026. CA Cancer J Clin. (2026) 76 (1): e70043. doi:10.3322/caac.70043
- 7. GBD 2023 Childhood Cancer Collaborators. Global burden of cancer in children and adolescents aged 0–19 years, 1990–2023: a systematic analysis for the global burden of disease study 2023. Lancet. (2026) 407 (10536): 1360 – 73. doi:10.1016/S0140-6736(26)00200-X
- 8. Gupta S, Rivera-Luna R, Ribeiro RC, Howard SC. Pediatric oncology as the next global child health priority: the need for national childhood cancer strategies in low- and middle-income countries. PLoS Med. (2014) 11 (6): e1001656. doi:10.1371/journal.pmed.1001656
- 9. Botta L, Gatta G, Didonè F, Lopez Cortes A, Pritchard-Jones K. BENCHISTA Project working group. International benchmarking of childhood cancer survival by stage at diagnosis: the BENCHISTA project protocol. PLoS One. (2022) 17 (11): e0276997. doi:10.1371/journal.pone.0276997
- 10. Bhakta N, Force LM, Allemani C, Atun R, Bray F, Coleman MP. Childhood cancer burden: a review of global estimates. Lancet Oncol. (2019) 20 (1): e42 – 53. doi:10.1016/S1470-2045(18)30761-7
- 11. Ramirez O, Aristizabal P, Zaidi A, Ribeiro RC, Bravo LE, on behalf of the VIGICANCER Working Group. Implementing a childhood cancer outcomes surveillance system within a population-based cancer registry. J Glob Oncol. (2018) 4: 1 – 11. doi:10.1200/JGO.17.00193
- 12. Cerda Jiménez P, Gajardo Ramírez ME, Rojas Muñoz FM, Robles Rojo PN, Rivera Vivian EC, Núñez Gómez KG. Registro nacional de cáncer infantil (RENCI): trienio 2017–2019. Medwave. (2024) 24 (Suppl 1): eSP011. doi:10.5867/medwave.2024.S1.SP011
- 13. Dufort Y, Álvarez G. Epidemiología del cáncer en niños y adolescentes en Uruguay: 20082012: un estudio de registro poblacional. Arch Pediatr Urug. (2021) 92 (1): 7 – 9. doi:10.31134/ap.92.1.3
- 14. Fritz AG. International Classification of Diseases for Oncology: ICD-O. Geneva: World Health Organization (2000).
- 15. Argentine Oncopediatric Registry (ROHA). 25 Years of the Argentine Oncopediatric Registry. Buenos Aires: National Cancer Institute (2025).
- 16. Dirección de Estadísticas e Información de Salud (DEIS). Estadísticas vitales: información básica. Argentina – Año 2022. Serie 5, Número 66. Buenos Aires: Ministerio de Salud de la Nación (2024). Available online at: (Accessed May 29 2026)
- 17. Instituto Nacional de Estadística y Censos (INDEC). Censo Nacional de Población, Hogares y Viviendas 2010: pueblos originarios. Buenos Aires: INDEC (2015). Available online at: (Accessed May 29 2026)
- 18. Moreno F, Loria D, Abriata G, Terracini B, ROHA network. Childhood cancer: incidence and early deaths in Argentina, 2000–2008. Eur. J. Cancer. (2013) 49 (2): 465 – 73. doi:10.1016/j.ejca.2012.08.001
- 19. Parkin DM. Cancer Incidence in Five Continents. Vol. XI. Lyon: IARC (2021).
- 20. Steliarova-Foucher E, Stiller C, Lacour B, Kaatsch P. International classification of childhood cancer, third edition. Cancer. (2005) 103 (7): 1457 – 67. doi:10.1002/cncr.20910
- 21. Instituto Nacional de Estadística y Censos (INDEC). Censo Nacional de Población, Hogares y Viviendas 2022: resultados definitivos. Buenos Aires: INDEC (2024). Available online at: (Accessed May 29 2026)
- 22. Segi M. Cancer Mortality for Selected Sites in 24 Countries (1950–1957). Sendai: Tohoku University School of Public Health (1960).
- 23. Sultan I, Alfaar AS, Sultan Y, Salman Z, Qaddoumi I. Trends in childhood cancer: incidence and survival analysis over 45 years of SEER data. PLoS One. (2025) 20 (1): e0314592. doi:10.1371/journal.pone.0314592
- 24. Vaccarella S, Franceschi S, Bray F, Wild CP, Plummer M, Dal Maso L. Worldwide thyroid-cancer epidemic? The increasing impact of overdiagnosis. N. Engl. J. Med.. (2016) 375 (7): 614 – 7. doi:10.1056/NEJMp1604412
- 25. Pritchard-Jones K, Pieters R, Reaman GH, Hjorth L, Downie P, Calaminus G. Sustaining innovation and improvement in the treatment of childhood cancer: lessons from high-income countries. Lancet Oncol. (2013) 14 (2): e95 – 103. doi:10.1016/S1470-2045(13)70010-X
- 26. Gatta G, Botta L, Rossi S, Aareleid T, Bielska-Lasota M, Clavel J. Childhood cancer survival in Europe 1999–2007: results of EUROCARE-5-a population-based study. Lancet Oncol. (2014) 15 (1): 35 – 47. doi:10.1016/S1470-2045(13)70548-5
- 27. Steliarova-Foucher E, Fidler MM, Colombet M, Lacour B, Kaatsch P, Piñeros M. Changing geographical patterns and trends in cancer incidence in children and adolescents in Europe. Lancet Oncol. (2018) 19 (9): 1159 – 69. doi:10.1016/S1470-2045(18)30423-6
- 28. Steliarova-Foucher E, Colombet M, Ries LAG, Moreno F, Dolya A, Shin HY. International Incidence of Childhood Cancer, Volume III. Lyon: International Agency for Research on Cancer (2025). In press.
- 29. Malvezzi M, Santucci C, Alicandro G, Carioli G, Boffetta P, Ribeiro KB. Childhood cancer mortality trends in the americas and Australasia: an update to 2017. Cancer. (2021) 127 (18): 3445 – 56. doi:10.1002/cncr.33642
- 30. Magrath I, Steliarova-Foucher E, Epelman S, Ribeiro RC, Harif M, Li CK. Paediatric cancer in low-income and middle-income countries. Lancet Oncol. (2013) 14 (3): e104 – 16. doi:10.1016/S1470-2045(13)70008-1
- 31. CureAll framework: WHO Global Initiative for Childhood Cancer. Increasing Access, Advancing Quality, Saving Lives. Geneva: World Health Organization (2021). Licence: CC BY-NC-SA 3.0 IGO; Available online at: (Accessed October 28, 2021).
- 32. Daltveit DS, Morgan E, Bardot A, Steliarova-Foucher E, Damie A, Hagenimana M. Childhood cancer survival in Africa, Asia, Latin America and the Caribbean, during 2008–2017 (SURVCAN-3): a population-based benchmarking study of 16,821 children. J Natl Cancer Inst. (2025) 118: 1183 – 94. doi:10.1093/jnci/djaf321
- 33. Erdmann F, Feychting M, Mogensen H, Schmiegelow K, Zeeb H. Social inequalities along the childhood cancer Continuum: an overview of evidence and a conceptual framework to identify underlying mechanisms and pathways. Front. Public Health. (2019) 7: 84. doi:10.3389/fpubh.2019.00084
- 34. Kutluk T. Monitoring progress in global childhood cancer survival. Lancet. (2026) 407: 1304 – 5. doi:10.1016/S0140-6736(26)00561-1
- 35. Vásquez L, Fuentes-Alabí S, Loggetto P, Benitez-Majano S, Metzger ML, Jarquin-Pardo M. Advances in the global initiative for childhood cancer: implementation in Latin America and the Caribbean. Rev. Panam. Salud Publica. (2023) 47: e128. doi:10.26633/RPSP.2023.128
Citation
Moreno, F., et al. (2026). Childhood cancer incidence, survival and mortality patterns in Argentina, 2000–2022: from the Argentine Oncopediatric Registry (ROHA). Frontiers in Cancer Control and Society, Volume 4. https://doi.org/
- Received
- Accepted
- Published
- Volume
- 4 - 2026
Copyright
© 2026 Moreno, Chaplin, Nana and Abriata.
License: https://creativecommons.org/licenses/by/4.0/
*Correspondence: Florencia Moreno
Article metrics
- Views
- 0
- Downloads
- 0
- Citations
- 0
- Shares
- 0
