Reproducibility, reliability and validity of population-based administrative health data for the assessment of cancer non-related comorbidities

Abstract

BackgroundPatients with comorbidities do not receive optimal treatment for their cancer, leading to lower cancer survival. Information on individual comorbidities is not straightforward to derive from population-based administrative health datasets. We described the development of a reproducible algorithm to extract the individual Charlson index comorbidities from such data. We illustrated the algorithm with 1,789 laryngeal cancer patients diagnosed in England in 2013. We aimed to clearly set out and advocate the time-related assumptions specified in the algorithm by providing empirical evidence for them.MethodsComorbidities were assessed from hospital records in the ten years preceding cancer diagnosis and internal reliability of the hospital records was checked. Data were right-truncated 6 or 12 months prior to cancer diagnosis to avoid inclusion of potentially cancer-related comorbidities. We tested for collider bias using Cox regression.ResultsOur administrative data showed weak to moderate internal reliability to identify comorbidities (ICC ranging between 0.1 and 0.6) but a notably high external validity (86.3%). We showed a reverse protective effect of non-cancer related Chronic Obstructive Pulmonary Disease (COPD) when the effect is split into cancer and non-cancer related COPD (Age-adjusted HR: 0.95, 95% CI:0.7–1.28 for non-cancer related comorbidities). Furthermore, we showed that a window of 6 years before diagnosis is an optimal period for the assessment of comorbidities.ConclusionTo formulate a robust approach for assessing common comorbidities, it is important that assumptions made are explicitly stated and empirically proven. We provide a transparent and consistent approach useful to researchers looking to assess comorbidities for cancer patients using administrative health data.

Association between age, deprivation and specific comorbid conditions and the receipt of major surgery in patients with non-small cell lung cancer in England: A population-based study

“…However, a limitation of the study is related to the information used for comorbidity, which is derived from the HES datasets 17. Thus, we do not know the comorbidity status for patients who never attended secondary care, and assume they do not have any comorbidities.…”

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The pattern of Comorbidities and Associated Risk Factors among Colorectal Cancer Patients in Spain: CoMCoR study

“…We recorded information regarding the cancer stage at diagnosis (TNM staging system, 7 th edition), cancer diagnostic exams, tumor morphology, cancer treatment, patients' comorbidities, performance status, and vital status. All recorded comorbidities were extracted 6 months before the index cancer was diagnosed, based on a standardized protocol published elsewhere [16]. All information was classified as either patient, tumor, or healthcare factors.…”

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