ArticleCanadian Urological Association journal = Journal de l'Association des urologues du Canada2017
The value of complementing administrative data with abstracted information on smoking and obesity: A study in kidney cancer.
Article in Canadian Urological Association journal = Journal de l'Association des urologues du Canada, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Inverse Probability of Treatment Weighting (Propensity Score) using the Military Health System Data Repository and National Death Index.Journal of visualized experiments : JoVE · 2020Article
- Article
- Impact of Statins on Cardiovascular Outcomes Following Coronary Artery Calcium Scoring.Journal of the American College of Cardiology · 2018Observational
- In search of the perfect model.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2017Article
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionVariables, such as smoking and obesity, are rarely available in administrative databases. We explored the added value of including these data in an administrative database study evaluating the association of statin use with survival in kidney cancer.
methodsWe linked administrative data with chart-abstracted data on smoking and obesity for 808 patients undergoing nephrectomy for kidney cancer. Base models consisted of variables from administrative databases (age, sex, year of surgery, and different measures of comorbidity [to compare their sensitivity to smoking and obesity data]); extended models added chart-abstracted data. We compared coefficients for statin use with overall (OS) and cancer-specific survival (CSS), and used the c-statistic and net reclassification improvement (NRI) to compare predications of five-year survival obtained from Cox proportional hazard models.
resultsThe coefficient for statin use changed minimally following addition of abstracted data (<6% for OS, <2% for CSS). Base models performed similarly for OS, with c-statistics of 0.75 (95% confidence interval [CI] 0.72-0.79) for Charlson score and 0.73 (95% CI 0.69-0.78) for John Hopkins Aggregated Diagnosis Groups score. After including abstracted data, c-statistics modestly improved (change <0.02); CSS demonstrated similar findings. NRIs were 0.210 (95% CI 0.062-0.297) and 0.186 (-0.031-0.387) when using the Charlson score, and 0.207 (0.068-0.287) and 0.197 (0.007-0.399) when using the Aggregated Diagnosis Groups score, for OS and CSS, respectively.
conclusionsThe inclusion of data on smoking and obesity marginally influences survival models in kidney cancer studies using administrative data.
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Registered trials
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