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Although the real-life benefits of bevacizumab may differ from clinical trials, observational data are rare. In this cohort study, the effectiveness of bevacizumab in first-line treatment of metastatic colorectal cancer was investigated. Patients initiating bevacizumab between January 2006 and December 2007 were identified in 28 French centres. Outcomes were investigated in the whole cohort and in those with irinotecan-based treatment that was used in the pivotal clinical trial; patients were stratified using inclusion/exclusion criteria of the pivotal clinical trial (PCT) (eligible for the PCT, not eligible or unclassifiable). The Kaplan-Meier method estimated progression-free survival (PFS) and overall survival (OS). A total of 411 patients were included: 57 % male, median age 65.1 years, 78 % Eastern Cooperative Oncology Group performance status ≤1, 88 % irinotecan-based regimen, median duration of bevacizumab use 5.5 months, median OS = 25.3 months (95 % confidence interval, CI [23.3; 27.0]) and median PFS = 10.1 months (95 % CI [9.5; 11.0]). Among the 360 patients who received irinotecan-based chemotherapy, 144 would have been eligible for the PCT, 194 not eligible and 22 unclassifiable. Median OS in those considered eligible was 29.1 (95 % CI [25.4; 33.6]) and in those considered not eligible this was 24.9 months (95 % CI [21.3; 26.9]); median PFS was respectively 11.5 months (95 % CI [10.3; 12.0]) and 9.4 months (95 % CI [8.8; 10.3]). The effectiveness of bevacizumab was found to be similar to that found in other studies including clinical trials which is reassuring.

Background Diagnosis performances of case-identifying algorithms developed in healthcare database are usually assessed by comparing identified cases with an external data source. When this is not feasible, intra-database validation can present an appropriate alternative. Objectives To illustrate through two practical examples how to perform intra-database validations of case-identifying algorithms using reconstituted Electronic Health Records (rEHRs). Methods Patients with 1) multiple sclerosis (MS) relapses and 2) metastatic castration-resistant prostate cancer (mCRPC) were identified in the French nationwide healthcare database (SNDS) using two case-identifying algorithms. A validation study was then conducted to estimate diagnostic performances of these algorithms through the calculation of their positive predictive value (PPV) and negative predictive value (NPV). To that end, anonymized rEHRs were generated based on the overall information captured in the SNDS over time (e.g. procedure, hospital stays, drug dispensing, medical visits) for a random selection of patients identified as cases or non-cases according to the predefined algorithms. For each disease, an independent validation committee reviewed the rEHRs of 100 cases and 100 non-cases in order to adjudicate on the status of the selected patients (true case/ true non-case), blinded with respect to the result of the corresponding algorithm. Results Algorithm for relapses identification in MS showed a 95% PPV and 100% NPV. Algorithm for mCRPC identification showed a 97% PPV and 99% NPV. Conclusion The use of rEHRs to conduct an intra-database validation appears to be a valuable tool to estimate the performances of a case-identifying algorithm and assess its validity, in the absence of alternative.

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