Trends in long-term cancer survival in Cali Colombia: 1998-2017

COLOMBIA MEDICA(2022)

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摘要
Background: Population-based cancer survival is an indicator of the effectiveness of cancer services that reflects the survival of all cancer patients in the population, regardless of socioeconomic status and disease characteristics. Aim: Provision of an up-to-date survival estimate of patients recorded within Cali Population Cancer Registry (RPCC) in 1998-2017. As a second objective, results will be compared with those reported by the CONCORD study for cancers prioritized by the current Ten-Year Cancer Control Plan of Colombia, 2012-2021. Methods: Adult cancer cases (aged 15 to 99 years) for nine cancer types diagnosed between 1998 and 2017, with follow-up to 2018, were obtained from the RPCC. The 5-year age-standardized net survival estimates (NS) were estimated using the Pohar-Perme. The results for the period 1995- 2014 were compared with those reported by the CONCORD study for the following locations: stomach (C16), breast (C50), cervix (C53), prostate (C61), and lung (C33-34). Results: Five-year survival estimates for breast and prostate cancers improved ten percentage points through 2007 (70.8 to 81.1 for breast and 79.9 to 90.2 for prostate) and remained stable during 2008-2017. For cervical cancer, survival estimates has remained stable for the last two decades at 53%. For stomach cancer and lung cancer, five-year NS was lower than 25% over the study period. For colorectal cancer, survival estimates increased from 37.9% in 1998-2002 to 54.8% in 2013-2017. Compared to previous 5-year survival estimates of cases diagnosed in 2010-2014, the estimates in this study are significantly higher than those obtained by CONCORD. Survival estimates of patients diagnosed in 1995-2009 showed no difference to CONCORD study. Conclusions: Periodic update of vital status and date of last contact reduces bias in survival estimates in population-based cancer registries with passive follow-up.
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关键词
Cali, Cancer, Colombia, bias, net survival, epidemiology, cancer, led bias
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