Translating results from randomized trials to individual patients is challenging since treatment effects may vary due to heterogeneous prognostic characteristics. We aimed to demonstrate model development for individualized treatment effect predictions in cancer patients. We used data from two randomized trials that investigated combination (ComC) versus sequential chemotherapy (SeqC) in unresectable metastatic colorectal cancer (mCRC) patients.
We used data from 803 patients included in CAIRO for prediction model development and internal validation, and data from 1423 patients included in FOCUS for external validation. A Weibull model with prespecified patient and tumour characteristics was developed for a prediction of gain in median overall survival by upfront ComC versus SeqC. Decision curve analysis with net benefit was used. A nomogram was built for estimating the probability of receiving second-line treatment after first-line monochemotherapy.
Median predicted gain in overall survival for ComC versus SeqC was 2.3 months (IQR -1.1-3.7 months). A gain in favour of SeqC was found in 231 patients (29%) and a gain of > 3 months for ComC in 294 patients (37%). Patients with benefit from SeqC had metachronous metastatic disease and a left-sided primary tumour. Decision curve analyses showed improvement in net benefit for treating all patients according to prediction-based treatment compared to treating all patients with ComC. Multiple characteristics were identified as prognostic variables that identify patients at risk of never receiving second-line treatment if treated with initial monochemotherapy. External validation showed good calibration with moderate discrimination in both models (C-index 0.66 and 0.65, respectively).
We successfully developed individualized prediction models including prognostic characteristics derived from randomized trials to estimate treatment effects in mCRC patients. In times where the heterogeneity of CRC becomes increasingly evident, such tools are an important step towards personalized treatment.
Clinical trial identification
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M. Koopman: Research grant / Funding (institution): Dutch Colorectal Cancer Group; Advisory / Consultancy: Servier. J.J. Kwakman: Honoraria (self), Research grant / Funding (institution): Nordic Pharma; Advisory / Consultancy, Research grant / Funding (institution): Servier. C.J.A. Punt: Research grant / Funding (institution): Dutch Colorectal Cancer Group; Advisory / Consultancy: Servier. All other authors have declared no conflicts of interest.