2 research outputs found
Patient-Reported Morbidity Instruments: A Systematic Review
Objectives: Although comorbidities play an essential role in risk adjustment and outcomes measurement, there is little consensus regarding the best source of this data. The aim of this study was to identify general patient-reported morbidity instruments and their measurement properties. Methods: A systematic review was conducted using multiple electronic databases (Embase, Medline, Cochrane Central, and Web of Science) from inception to March 2018. Articles focusing primarily on the development or subsequent validation of a patient-reported morbidity instrument were included. After including relevant articles, the measurement properties of each morbidity instrument were extracted by 2 investigators for narrative synthesis. Results: A total of 1005 articles were screened, of which 34 eligible articles were ultimately included. The most widely assessed instruments were the Self-Reported Charlson Comorbidity Index (n = 7), the Self-Administered Comorbidity Questionnaire (n = 3), and the Disease Burden Morbidity Assessment (n = 3). The most commonly included conditions were diabetes, hypertension, and myocardial infarction. Studies demonstrated substantial variability in item-level reliability versus the gold standard medical record review (κ range 0.66-0.86), meaning that the accuracy of the self-reported comorbidity data is dependent on the selected morbidity. Conclusions: The Self-Reported Charlson Comorbidity Index and the Self-Administered Comorbidity Questionnaire were the most frequently cited instruments. Significant variability was observed in reliability per comorbid condition of patient-reported morbidity questionnaires. Further research is needed to determine whether patient-reported morbidity data should be used to bolster medical records data or serve as a stand-alone entity when risk adjusting observational outcomes data
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Novel genomic signature predictive of response to immune checkpoint blockade: A pan-cancer analysis from project Genomics Evidence Neo-plasia Information Exchange (GENIE)
•High tumor mutation burden can be predictive of better response to immune checkpoint blockade but varies across cancers and has inconsistent definitions.•Genomic alterations in 16 genes that clustered into neuronal development/differentiation (PTPRD, NTRK3, ZFHX3, NOTCH3, EPHA5, EPHA7), receptor tyrosine kinase/phosphatase signaling (EPHA5, PTPRD, NTRK3, LATS1, PPM1D, EPHA7), and epigenetic regulation (ARID1A, TET1, SETD2, CREBBP, CIC, POLE) were associated with survival in patients treated with immune checkpoint blockade.•The ImmGA signature is predictive of response to immune checkpoint blockade.
Background: High tumor mutation burden (TMB) and total mutation count (TMC) can be predictive of better response to immune checkpoint blockade (ICB). Nevertheless, TMB and TMC are limited by variation across cancers and inconsistent definitions due to different profiling methods (targeted vs whole genome sequencing). Our objective was to identify genomic alterations (GAs) associated with ICB response and builds a novel genomic signature predictive of ICB response, independent of TMB/TMC.
Methods: This was a pan-cancer next generation sequencing (NGS)-association study using January 2014-May 2016 data from AACR Project Genomics Evidence Neo-plasia Information Exchange (GENIE). Participants included 6619 patients with metastatic or un-resectable cancer across 9 cancer types (including 1572 ICB-treated patients). GA data was collected using next-generation sequencing (NGS) assays and downloaded from cbioportal.org. Predictive analyses for ICB response were performed to develop the signature (ImmGA).
Results: GAs in 16 genes were associated with improved OS in ICB-treated patients (p < 0.005). 13 GAs were associated with an OS benefit in ICB-treated patients (Pinteraction < 0.05); these genes composed the ImmGA signature. High ImmGA score (≥2 alterations out of 13 predictive GAs) was associated with better OS in ICB-treated patients (AHR:0.67, 95%CI [0.6–0.75], p = 1.4e−12), even after accounting for TMC (Pinteraction = 8e−16). High ImmGA was associated with better OS in ICB-treated patients across most cancers and across different ICB treatment modalities.
Conclusion: A novel signature predictive of ICB response (ImmGA) was developed from 13 GAs. Further investigation of the utility of ImmGA for treatment and trial selection is warranted