Journal Article
Research Support, Non-U.S. Gov't
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Childhood cancer in Argentina: Survival 2000-2007.

INTRODUCTION: Information on the epidemiology of childhood cancer in Latin America is limited. The Argentinean Oncopaediatric Registry (ROHA) is a population-based registry active since 2000. This paper describes the 3-year survival experience of children diagnosed with cancer in Argentina during 2000-2007 by major morphological subgroup, age, sex, and geographical region of residence.

METHODS: Newly diagnosed paediatric cancer cases are registered in ROHA (estimated coverage is 93% of the country's cases). Three-year overall survival was estimated using Kaplan-Meier methods. Univariate Cox models were used to compare subgroup survival.

RESULTS: Between 2000 and 2007, a total of 10,181 new cancer diagnoses in children aged 0-14 years were reported to the registry. Three-year overall survival (95%CI) for all cancers was 61.7% (60.7; 62.7). Specific survival for the most frequent morphological types was: leukaemias 63.3% (61.6; 64.9), lymphomas and related neoplasms 75.3% (72.7; 77.7), brain neoplasms 46.3% (43.9; 48.7), soft-tissue sarcomas 52.3% (48.0; 56.5), neuroblastomas 49.6% (44.6; 54.3), renal tumours 76.7% (72.2; 80.6), and malignant bone tumours 47.2% (42.3; 51.9). Overall survival was associated with age but not sex and varied by geographical region. Compared to other regions, patients who resided in the capital city had a significantly higher survival: 69.6% (65.8; 73.0) versus 63.5% (59.4; 67.4) in Patagonia, 63.2% (61.9; 64.5) in the central region, 58.0% (54.2; 61.7) in Cuyo, 55.6% (52.5; 58.6) in the north-east, and 55.4% (52.4; 58.2) in the north-west (all P values <0.005).

CONCLUSIONS: Of children diagnosed with cancer in Argentina, 62% survived at least 3 years after diagnosis. Even though this figure is lower than that reported for more developed countries, survival patterns by diagnosis, age and sex were quite similar. Survival was lower in the two northern regions, which are areas with higher poverty levels.

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