Development and validation of a coding framework to identify severe acute toxicity from systemic anti-cancer therapy using hospital administrative data
Authors
Boyle, J. M.Cowling, T. E.
Kuryba, A.
Fearnhead, N. S.
van der Meulen, J.
Braun, M. S.
Walker, K.
Aggarwal, A.
Affiliation
Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK. Electronic address: jboyle@rcseng.ac.uk. Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK. Electronic address: thomas.cowling@lshtm.ac.uk. Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK. Electronic address: akuryba@rcseng.ac.uk. Department of Colorectal Surgery, Cambridge University Hospitals, Cambridge, UK. Electronic address: nicola.fearnhead@cambridgecolorectal.org. Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK. Electronic address: jan.vandermeulen@lshtm.ac.uk. Department of Oncology, The Christie NHS Foundation Trust, School of Medical Sciences, University of Manchester Manchester, UK. Electronic address: michael.braun@nhs.net. Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London, UK; Clinical Effectiveness Unit, Royal College of Surgeons of England, London, UK. Electronic address: kate.walker@lshtm.ac.uk. Department of Oncology, Guy's and St. Thomas' NHS Foundation Trust, London, UK. Electronic address: ajay.aggarwal@lshtm.ac.uk.Issue Date
2022
Metadata
Show full item recordAbstract
Background The capture of toxicities from systemic anti-cancer therapy (SACT) in real-world data will complement results from clinical trials. The aim of this study was to develop and validate a comprehensive coding framework to identify severe acute toxicity in hospital administrative data. Methods A coding framework was developed to identify diagnostic codes representing severe acute toxicity in hospital administrative data. The coding framework was validated on a sample of 23,265 colon cancer patients treated in the English National Health Service between 1 June 2014 and 31 December 2017. This involved comparing individual toxicities according to the receipt of SACT and according to different SACT regimens, as well as assessing the associations of predictive factors and outcomes with toxicity. Results The severe acute toxicities captured by the developed coding framework were shown to vary across clinical groups with an overall rate of 26.4% in the adjuvant cohort, 53.4% in the metastatic cohort, and 12.5% in the comparison group receiving no chemotherapy. Results were in line with regimen-specific findings from clinical trials. For example, patients receiving additional bevacizumab had higher rates of bleeding (12.5% vs. 2.7%), gastrointestinal perforation (5.6% vs. 2.9%) and fistulation (1.4% vs. 0.5%), and allergic drug reactions (1.4% vs. 0.5%). Severe acute toxicity was associated with pre-existing renal (p = 0.001) and cardiac disease (p = 0.038), and urgency of surgery (p = 0.004). Severe toxicity also predicted lower rates of completion of chemotherapy (p = <0.001) and an increased likelihood of altered administration route (p = <0.001). Conclusion These results demonstrate that the developed coding framework captures severe acute toxicities from hospital administrative data of colon cancer patients. A similar approach can be used for patients with other cancer types, receiving different regimens. Toxicity captured in administrative data can be used to compare treatment outcomes, inform clinical decision making, and provide opportunities for benchmarking and provider performance monitoring.Citation
Boyle JM, Cowling TE, Kuryba A, Fearnhead NS, van der Meulen J, Braun MS, et al. Development and validation of a coding framework to identify severe acute toxicity from systemic anti-cancer therapy using hospital administrative data. Vol. 77, Cancer Epidemiology. Elsevier BV; 2022. p. 102096.Journal
Cancer EpidemiologyDOI
10.1016/j.canep.2022.102096PubMed ID
35030349Additional Links
https://dx.doi.org/10.1016/j.canep.2022.102096Type
ArticleLanguage
enae974a485f413a2113503eed53cd6c53
10.1016/j.canep.2022.102096