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Editorial peer review is universally used but little studied. We examined the relationship between external reviewers' recommendations and the editorial outcome of manuscripts undergoing external peer-review at the Journal of General Internal Medicine (JGIM). We examined reviewer recommendations and editors' decisions at JGIM between 2004 and 2008. For manuscripts undergoing peer review, we calculated chance-corrected agreement among reviewers on recommendations to reject versus accept or revise. Using mixed effects logistic regression models, we estimated intra-class correlation coefficients (ICC) at the reviewer and manuscript level. Finally, we examined the probability of rejection in relation to reviewer agreement and disagreement. The 2264 manuscripts sent for external review during the study period received 5881 reviews provided by 2916 reviewers; 28% of reviews recommended rejection. Chance corrected agreement (kappa statistic) on rejection among reviewers was 0.11 (p<.01). In mixed effects models adjusting for study year and manuscript type, the reviewer-level ICC was 0.23 (95% confidence interval [CI], 0.19-0.29) and the manuscript-level ICC was 0.17 (95% CI, 0.12-0.22). The editors' overall rejection rate was 48%: 88% when all reviewers for a manuscript agreed on rejection (7% of manuscripts) and 20% when all reviewers agreed that the manuscript should not be rejected (48% of manuscripts) (p<0.01). Reviewers at JGIM agreed on recommendations to reject vs. accept/revise at levels barely beyond chance, yet editors placed considerable weight on reviewers' recommendations. Efforts are needed to improve the reliability of the peer-review process while helping editors understand the limitations of reviewers' recommendations.

Editorial peer review is universally used but little studied. We examined the relationship between external reviewers' recommendations and the editorial outcome of manuscripts undergoing external peer-review at the Journal of General Internal Medicine (JGIM). We examined reviewer recommendations and editors' decisions at JGIM between 2004 and 2008. For manuscripts undergoing peer review, we calculated chance-corrected agreement among reviewers on recommendations to reject versus accept or revise. Using mixed effects logistic regression models, we estimated intra-class correlation coefficients (ICC) at the reviewer and manuscript level. Finally, we examined the probability of rejection in relation to reviewer agreement and disagreement. The 2264 manuscripts sent for external review during the study period received 5881 reviews provided by 2916 reviewers; 28% of reviews recommended rejection. Chance corrected agreement (kappa statistic) on rejection among reviewers was 0.11 (p<.01). In mixed effects models adjusting for study year and manuscript type, the reviewer-level ICC was 0.23 (95% confidence interval [CI], 0.19-0.29) and the manuscript-level ICC was 0.17 (95% CI, 0.12-0.22). The editors' overall rejection rate was 48%: 88% when all reviewers for a manuscript agreed on rejection (7% of manuscripts) and 20% when all reviewers agreed that the manuscript should not be rejected (48% of manuscripts) (p<0.01). Reviewers at JGIM agreed on recommendations to reject vs. accept/revise at levels barely beyond chance, yet editors placed considerable weight on reviewers' recommendations. Efforts are needed to improve the reliability of the peer-review process while helping editors understand the limitations of reviewers' recommendations.

Editorial peer review is universally used but little studied. We examined the relationship between external reviewers' recommendations and the editorial outcome of manuscripts undergoing external peer-review at the Journal of General Internal Medicine (JGIM). We examined reviewer recommendations and editors' decisions at JGIM between 2004 and 2008. For manuscripts undergoing peer review, we calculated chance-corrected agreement among reviewers on recommendations to reject versus accept or revise. Using mixed effects logistic regression models, we estimated intra-class correlation coefficients (ICC) at the reviewer and manuscript level. Finally, we examined the probability of rejection in relation to reviewer agreement and disagreement. The 2264 manuscripts sent for external review during the study period received 5881 reviews provided by 2916 reviewers; 28% of reviews recommended rejection. Chance corrected agreement (kappa statistic) on rejection among reviewers was 0.11 (p<.01). In mixed effects models adjusting for study year and manuscript type, the reviewer-level ICC was 0.23 (95% confidence interval [CI], 0.19-0.29) and the manuscript-level ICC was 0.17 (95% CI, 0.12-0.22). The editors' overall rejection rate was 48%: 88% when all reviewers for a manuscript agreed on rejection (7% of manuscripts) and 20% when all reviewers agreed that the manuscript should not be rejected (48% of manuscripts) (p<0.01). Reviewers at JGIM agreed on recommendations to reject vs. accept/revise at levels barely beyond chance, yet editors placed considerable weight on reviewers' recommendations. Efforts are needed to improve the reliability of the peer-review process while helping editors understand the limitations of reviewers' recommendations.

ObjectivesAnnual cognitive screening in older adults is essential for early detection of cognitive impairment, yet primary care settings face time constraints that present barriers to routine screening. MyCog Mobile is a self-administered, smartphone-based cognitive screener that has the potential to help overcome these screening obstacles. We compared MyCog Mobile to ‘gold-standard’ measures to support its reliability and validity and examined performance differences between in-person versus remote assessment.DesignCross-sectional convenience sample study comparing MyCog Mobile measures to established cognitive assessments.SettingFive in-person research facility locations in Georgia, Texas, New Jersey, Florida and Arizona.Participants200 adults aged 65–87 years (M=72.56, SD=5.11) who spoke English.Primary outcome measuresConvergent and divergent validity were examined via Spearman’s rho correlations between MyCog Mobile measures (MyPictures, MyFaces, MySorting and MySequences) and established measures (verbal paired associates, digit span, letter-number sequencing, Color-Word Interference Test and Trail Making Test), as well as a confirmatory factor analysis using these same measures. Internal consistency was assessed via Spearman-Brown split-half correlations. Score distributions were compared between in-person and remote administration.ResultsInternal consistency for all MyCog Mobile measures was above acceptable thresholds, ranging from ρ=0.71 to 0.89. Strong correlations were found between MyCog Mobile subtests and their tablet counterparts (MyPictures-Picture Sequence Memory: ρ=0.52; MySorting-dimensional change card sorting: ρ=0.55). MyPictures and MyFaces demonstrated large correlations with convergent memory measures (verbal paired associates immediate ρ=0.51 and 0.56, respectively) and small correlations with discriminant measures. Confirmatory factor analysis supported a two-factor model with subtests loading onto episodic memory and executive functioning factors as expected (χ²(25)=39.136; Comparative Fit Index (CFI) = 0.965; Tucker–Lewis Index (TLI) = 0.950; Root Mean Square Error of Approximation (RMSEA) = 0.053; Standardized Root Mean Square Residual (SRMR) = 0.040). Remote participants scored significantly higher on the MyPictures task overall (t(249)=2.98, p=0.004), while in-person participants scored higher on the MyFaces First Letter subtest and MySequences.ConclusionsMyCog Mobile offers a reliable and valid assessment of executive functioning and episodic memory in older adults. Performance may differ by setting, but further research is needed. These findings support future clinical validation studies to determine the diagnostic accuracy of MyCog Mobile to detect cognitive impairment.

Background Understanding the mechanistic effects of novel immunotherapy agents is critical to improving their successful clinical translation. These effects need to be studied in preclinical models that maintain the heterogenous tumor microenvironment (TME) and dysfunctional cell states found in a patient’s tumor. We investigated immunotherapy perturbations targeting co-stimulatory molecule GITR and co-inhibitory immune checkpoint TIGIT in a patient-derived ex vivo system that maintains the TME in its near-native state. Leveraging single-cell genomics, we identified cell type-specific transcriptional reprogramming in response to immunotherapy perturbations. Methods We generated ex vivo tumor slice cultures from fresh surgical resections of gastric and colon cancer and treated them with GITR agonist or TIGIT antagonist antibodies. We applied paired single-cell RNA and TCR sequencing to the original surgical resections, control, and treated ex vivo tumor slice cultures. We additionally confirmed target expression using multiplex immunofluorescence and validated our findings with RNA in situ hybridization. Results We confirmed that tumor slice cultures maintained the cell types, transcriptional cell states and proportions of the original surgical resection. The GITR agonist was limited to increasing effector gene expression only in cytotoxic CD8 T cells. Dysfunctional exhausted CD8 T cells did not respond to GITR agonist. In contrast, the TIGIT antagonist increased TCR signaling and activated both cytotoxic and dysfunctional CD8 T cells. This included cells corresponding to TCR clonotypes with features indicative of potential tumor antigen reactivity. The TIGIT antagonist also activated T follicular helper-like cells and dendritic cells, and reduced markers of immunosuppression in regulatory T cells. Conclusions We identified novel cellular mechanisms of action of GITR and TIGIT immunotherapy in the patients’ TME. Unlike the GITR agonist that generated a limited transcriptional response, TIGIT antagonist orchestrated a multicellular response involving CD8 T cells, T follicular helper-like cells, dendritic cells, and regulatory T cells. Our experimental strategy combining single-cell genomics with preclinical models can successfully identify mechanisms of action of novel immunotherapy agents. Understanding the cellular and transcriptional mechanisms of response or resistance will aid in prioritization of targets and their clinical translation.

Objectives Self‐administered, user‐friendly apps that can detect initial symptoms of cognitive impairment have enormous potential to improve early detection of cognitive decline. We examine the psychometric properties of the redesigned version of MyCog, MyCog 2.0, an app‐based tool for older adults that assesses executive function and episodic memory. MyCog 2.0 aims to improve usability while maintaining the psychometric validity demonstrated in the original version. Methods Feedback from clinicians and patients on MyCog was gathered to inform the human‐centered design improvements of MyCog 2.0. To assess the psychometric properties of the improved tool, data from a community sample (n = 200; mean age = 73 years) who had completed MyCog 2.0 were compared to an age‐matched sample who had completed the original MyCog. Internal consistency and construct validity were evaluated via confirmatory factor analysis. Bayesian differential item functioning was employed to evaluate the evidence for equivalence of MyCog and MyCog 2.0. Results Internal consistency was high for executive function and episodic memory tests (ωt = 0.84). A two‐factor model showed excellent fit, demonstrating that tests measured two related yet distinct constructs, episodic memory and executive functioning, as expected. Differential item functioning between the two test versions was not observed for episodic memory performance or executive functioning accuracy; however, response time on five executive function items was found to differ across versions. Conclusions Findings support MyCog 2.0 as the first reliable self‐administered cognitive screener designed specifically for ease of use among older adults. Findings support the internal consistency and construct validity of MyCog 2.0 and provide a foundation for the forthcoming clinical validation studies.