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.
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.
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).
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.
Development of a diagnostic coding framework to identify severe acute chemotherapy toxicity.
Hospital administrative data used alongside a dedicated chemotherapy dataset.
Coding framework validated successfully in a large national sample of colon cancer patients.
Framework transferable to different systemic anti-cancer therapy agents and cancer types.
Vital for informing clinical practice, benchmarking, and quality improvement processes.
Given the widespread use of systemic anti-cancer therapy (SACT), the ability to measure and understand severe acute toxicities is vital for comparing different treatments and informing patient and clinician decision-making, as well as for facilitating the comparative assessment of toxicities across hospital settings to benchmark best practice and stimulate quality improvement.
A study in breast cancer patients showed a hospitalisation rate of 43% in those receiving SACT, with 75% of admissions confirmed as chemotherapy-related adverse events . Despite this significant burden of toxicity on patients and healthcare systems, there remains a lack of data related to real-world practice. Existing evidence usually comes from randomised controlled trials (RCTs) which can be limited in their application to real-world practice . First, there is evidence that acute toxicities are more common in real-world practice than in clinical trials . Second, RCTs often underrepresent patients who are older, comorbid, or less fit, and sometimes ethnic and socioeconomic groups too . Third, rare adverse events may be difficult to capture in RCTs with small sample sizes or short study durations.
To date, some studies of real-world practice have used medical note abstraction or diagnostic and procedural codes from insurance claims to identify acute toxicity . Medical note abstraction confers considerable time and cost implications and is impractical for ongoing monitoring. Insurance claims have been shown to provide inconsistent information about specific SACT regimens and incomplete data on the occurrence of events related to SACT .
Many studies of acute SACT toxicity in real-world practice are limited by their lack of generalisability because they only included patients who had a specific toxicity, disease stage, or SACT regimen, or they excluded patients based on age or insurance status . In addition, there is often a lack of granularity about SACT details such as administration dates which are important for ascertaining the precise timeframe during which acute toxicities may occur .
Most studies that attempted to validate coding frameworks were designed to identify acute toxicity from insurance claims or hospital administrative data in breast cancer patients . These studies have included only a small selection of toxicities, often not considering biologic therapies which have unique toxicity profiles.
The aim of our study was to develop a broad and comprehensive coding framework of severe acute toxicity (toxicity necessitating an overnight hospital admission) from SACT across a range of organ systems using hospital administrative data, covering different regimens including biologic therapies. The performance of this coding framework was validated in a large national population-based sample of colon cancer patients treated in the English National Health Service (NHS).