DISCUSSION
toxicity
DISEASE, SECONDARY
In this secondary analysis of the CO.17 trial, we demonstrate that a measure of patient-level time toxicity can be successfully extracted. In CO.17, despite a statistically significant OS benefit with cetuximab in the overall study population, the number of home days was similar across arms and patients receiving cetuximab spent three times as many days alive with health care contact compared with patients treated with supportive care alone. In the The primary objective of this work was to demonstrate the feasibility of collecting and comparing time toxicity from a completed RCT. We have previously calculated the estimated time toxicity of treatments from trial protocols and publications, but this work was limited by the lack of patient-level data.The primary finding of this work is that despite a statistically significant OS benefit with cetuximab, time toxicity eroded into its survival benefit. In the overall population, home days were similar across arms. Results were even more striking for patients with Patients receiving this treatment on average live 6 weeks longer.Patients receiving this treatment on average live 6 weeks longer. However, patients getting the treatment spend more time coming to clinic and in the hospital—almost one in every 5th day will be spent in the clinic or hospital. Overall, patients getting the treatment spend the same number of days at home as patients focusing on symptom control alone.For truly effective treatments, time toxicity data can support treatments. At the time that CO.17 was conducted (2003-2005) and when initial survival results were first published (2007), the impact of In addition to the overall time toxicity data, the source of time toxicity can provide valuable insights. We found that planned visits accounted for approximately 50% of all time toxicity (and two thirds of the time toxicity for people with This work has several limitations. First, the current measure itself is imperfect. It does not capture time toxicity when the patient is home (eg, telemedicine and home-based infusions), associated with care logistics (eg, time spent on the phone with insurance company), and for care partners. It does not differentiate between the source and quality of contact days. It assumes that all home days are equally good, and all time toxic days are equally bad. A more nuanced measure, perhaps a quality-weighted time toxic days, is appealing, but we must consider the complexity in collecting, calculating, collating, and communicating it. Measures such as Q-TWiST (quality-adjusted time without symptoms of disease or toxicity) face an uphill battle for routine adoption because of these reasons.In conclusion, we demonstrate that measures of time toxicity can be successfully extracted through secondary analyses of completed RCTs. Information on time toxicity can supplement traditional survival end point reporting in clinical trials. Future work should refine the time toxicity measure and explore how to deploy it prospectively in clinical trials.