Abstract:
:The objective was to compare two techniques to estimate age in databases with incomplete records and analyze their application to the calculation of cancer incidence. The study used the database of the Population-Based Cancer Registry from the city of São Paulo, Brazil, containing cases of urinary tract cancer diagnosed from 1997 to 2013. Two techniques were applied to estimate age: correction factor and multiple imputation. Using binomial distribution, six databases were simulated with different proportions of incomplete data on patient's age (from 5% to 50%). The ratio between the incidence rates was calculated, using the complete database as reference, whose standardized incidence was 11.83/100,000; the other incidence rates in the databases, with at least 5% incomplete data for age, were underestimated. By applying the correction factors, the corrected rates did not differ from the standardized rates, but this technique does not allow correcting specific rates. Multiple imputation was useful for correcting the standardized and specific rates in databases with up to 30% of incomplete data, but the specific rates for individuals under 50 years of age were underestimated. Databases with 5% incomplete data or more require correction. Although the implementation of multiple imputation is complex, it proved to be superior to the correction factor. However, it should be used sparingly, since age-specific rates may remain underestimated. :O objetivo foi comparar duas técnicas para estimar idade em bancos de dados com registros incompletos e analisar sua aplicação no cálculo da incidência de câncer. Utilizou-se a base de dados do Registro de Câncer de Base Populacional do Município de São Paulo, Brasil, contendo casos diagnosticados por câncer do trato urinário, entre 1997 e 2013. Foram aplicadas duas técnicas para estimativa de idade: fator de correção e imputação múltipla. Foram simuladas, usando a distribuição binomial, seis bases de dados com diferentes proporções de dados incompletos para idade de 5% até 50%. A razão entre as incidências foi calculada tendo, como referência, a base completa, cuja incidência padronizada foi de 11,83/100 mil; as demais incidências nas bases com 5% ou mais de dados incompletos para idade apresentaram-se subestimadas. Ao aplicar o fator de correção, as taxas corrigidas não apresentaram diferenças em comparação com as padronizadas, entretanto, essa técnica não permite corrigir taxas específicas. A imputação múltipla foi útil na correção das taxas padronizadas e específicas em bancos com até 30% de dados incompletos, entretanto, as taxas específicas para indivíduos com menos de 50 anos apresentaram-se subestimadas. Bases com 5% ou mais de dados incompletos necessitam de aplicação de correção. A imputação múltipla, apesar de complexa em sua execução, mostrou-se superior ao fator de correção. Todavia, deve ser utilizada com parcimônia, pois taxas específicas por idade podem manter-se subestimadas. :El objetivo fue comparar dos técnicas para estimar edad en bancos de datos con registros incompletos y analizar su aplicación en el cálculo de la incidencia de cáncer. Se utilizó la base de datos del Registro de Cáncer de Base Poblacional del municipio de São Paulo, Brasil, conteniendo casos diagnosticados de cáncer del tracto urinario, entre 1997 y 2013. Se aplicaron dos técnicas para la estimativa de edad: factor de corrección e imputación múltiple. Fueron simuladas, usando una distribución binomial, seis bases de datos con diferentes proporciones de datos incompletos para edad desde un 5% hasta el 50%. La razón entre las incidencias se calculó teniendo, como referencia, la base completa, cuya incidencia padronizada fue de 11,83/100.000; las demás incidencias en las bases con un 5% o más de datos incompletos en la edad se presentaron subestimadas. Al aplicar el factor de corrección, las tasas corregidas no presentaron diferencias, en comparación con las estandarizadas, sin embargo, esta técnica no permite corregir tasas específicas. La imputación múltiple fue útil en la corrección de las tasas estandarizadas y específicas en bancos con hasta un 30% de datos incompletos, no obstante, las tasas específicas para individuos con menos de 50 años se presentaron subestimadas. Bases con un 5% o más de datos incompletos necesitan una aplicación de corrección. La imputación múltiple, a pesar de ser compleja en su ejecución, se mostró superior al factor de corrección. Sin embargo, debe ser utilizada con prudencia, puesto que las tasas específicas por edad pueden seguir manteniéndose subestimadas.
journal_name
Cad Saude Publicajournal_title
Cadernos de saude publicaauthors
Oliveira MM,Latorre MDRDO,Tanaka LF,Curado MPdoi
10.1590/0102-311X00140717subject
Has Abstractpub_date
2018-09-03 00:00:00pages
e00140717issue
6eissn
0102-311Xissn
1678-4464pii
S0102-311X2018000606002journal_volume
34pub_type
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