IntroductionReal-world evidence derived from electronic health records (EHRs) is increasingly recognized as a supplement to evidence generated from traditional clinical trials. In oncology, tumor-based Response Evaluation Criteria in Solid Tumors (RECIST) endpoints are standard clinical trial metrics. The best approach for collecting similar endpoints from EHRs remains unknown. We evaluated the feasibility of a RECIST-based methodology to assess EHR-derived real-world progression (rwP) and explored non-RECIST-based approaches.MethodsIn this retrospective study, cohorts were randomly selected from Flatiron Health’s database of de-identified patient-level EHR data in advanced non-small cell lung cancer. A RECIST-based approach tested for feasibility (N = 26). Three non-RECIST approaches were tested for feasibility, reliability, and validity (N = 200): (1) radiology-anchored, (2) clinician-anchored, and (3) combined. Qualitative and quantitative methods were used.ResultsA RECIST-based approach was not feasible: cancer progression could be ascertained for 23% (6/26 patients). Radiology- and clinician-anchored approaches identified at least one rwP event for 87% (173/200 patients). rwP dates matched 90% of the time. In 72% of patients (124/173), the first clinician-anchored rwP event was accompanied by a downstream event (e.g., treatment change); the association was slightly lower for the radiology-anchored approach (67%; 121/180). Median overall survival (OS) was 17 months [95% confidence interval (CI) 14, 19]. Median real-world progression-free survival (rwPFS) was 5.5 months (95% CI 4.6, 6.3) and 4.9 months (95% CI 4.2, 5.6) for clinician-anchored and radiology-anchored approaches, respectively. Correlations between rwPFS and OS were similar across approaches (Spearman’s rho 0.65–0.66). Abstractors preferred the clinician-anchored approach as it provided more comprehensive context.ConclusionsRECIST cannot adequately assess cancer progression in EHR-derived data because of missing data and lack of clarity in radiology reports. We found a clinician-anchored approach supported by radiology report data to be the optimal, and most practical, method for characterizing tumor-based endpoints from EHR-sourced data.FundingFlatiron Health Inc., which is an independent subsidiary of the Roche group.Electronic supplementary materialThe online version of this article (10.1007/s12325-019-00970-1) contains supplementary material, which is available to authorized users.

These data suggest a potential dose-response relationship between daily computer usage time and musculoskeletal symptoms.

Real-world evidence derived from electronic health records (EHRs) is increasingly recognized as a supplement to evidence generated from traditional clinical trials. In oncology, tumor-based Response Evaluation Criteria in Solid Tumors (RECIST) endpoints are collected in clinical trials. The best approach for collecting similar endpoints from EHRs remains unknown.We evaluated the feasibility of a traditional RECIST-based methodology to assess EHR-derived real-world progression (rwP) and explored non-RECIST-based approaches. In this retrospective study, cohorts were randomly selected from Flatiron Health's database of patient-level EHR data in advanced non-small cell lung cancer. A RECIST-based approach was tested for feasibility (N=26). Three non-RECIST abstraction approaches were tested for feasibility, reliability, and validity (N=200): (1) radiology-anchored, (2) clinician-anchored, and (3) combined.RECIST-based cancer progression could be ascertained from the EHRs of 23% of patients (6/26).In 87% of patients (173/200), at least one rwP event was identified using both the radiologyand clinician-anchored approaches. rwP dates matched 90% of the time. In 72% of patients (124/173), the first clinician-anchored rwP event was accompanied by a downstream event (e.g., treatment change); the association was slightly lower for the radiology-anchored approach (67%; 121/180). Median overall survival (OS) was 17 months (95% confidence interval [CI]: 14, 19). Median real-world progression-free survival (rwPFS) was 5.5 (95% CI: 4.6, 6.3) and 4.9 months (95% CI: 4.2, 5.6) for clinician-anchored and radiology-anchored approaches, respectively. Correlations between rwPFS and OS were similar across approaches (Spearman's rho: 0.65-0.66). Abstractors preferred the clinician-anchored approach as it provided more

Integrative computer usage monitors have become widely used in epidemiologic studies to investigate the exposure-response relationship of computer-related musculoskeletal disorders. These software programs typically estimate the exposure duration of computer use by summing precisely recorded durations of input device activities and durations of inactivity periods shorter than a predetermined activity duration cutoff value, usually 30 or 60 sec. The goal of this study was to systematically compare the validity of a wide range of cutoff values. Computer use activity of 20 office workers was observed for 4 consecutive hours using both a video camera and a usage monitor. Video recordings from the camera were analyzed using specific observational criteria to determine computer use duration. This observed duration then served as the reference and was compared with 238 estimates of computer use duration calculated from the usage monitor data using activity duration cutoffs ranging from 3 to 240 sec in 1-sec increments. Estimates calculated with cutoffs ranging from 28 to 60 sec were highly correlated with the observed duration (Spearman's correlation 0.87 to 0.92) and had nearly ideal linear relationships with the observed duration (slopes and r-squares close to one, and intercepts close to zero). For the same range of cutoff values, when the observed and estimated durations were compared for dichotomous exposure classification across participants, minimal exposure misclassification was observed. It is concluded that activity duration cutoffs ranging from 28 to 60 sec provided unbiased estimates of computer use duration.

A pilot study classified the locations, furniture, input devices and postures associated with using laptop computers in a small cohort of college students. Data were collected from digital photographs of the students posing as using laptop computers in their usual workstation configurations. The observed configurations were assigned to descriptive categories and the Rapid Upper Limb Assessment (RULA) assessed the postural risk factors observed on the participants. We observed that 75% of the participants used the laptop computer in the traditional table and chair configuration; 25% of the participants used the laptop computer in untraditional configurations where they placed the computer on their laps while sitting on a lounge type couch or in their bed. Excessive shoulder flexion (61% of all configurations) and neck flexion (35%) were the postural risk factors observed commonly. RULA scores suggested the need for further postural investigation.