Assessing real-world representativeness of prospective registry cohorts in oncology:insights from patients with esophagogastric cancer

Objectives: This study aimed to explore the real-world representativeness of a prospective registry cohort with active accrual in oncology, applying a representativeness metric that is novel to health care. Study Design and Setting: We used data from the Prospective Observational Cohort Study of Esophageal-Gastric Cancer Patients (POCOP) registry and from the population-based Netherlands Cancer Registry (NCR). We used Representativeness-indicators (R-indicators) and overall survival to investigate the degree to which the POCOP cohort and clinically relevant subgroups were a representative sample compared to the NCR database. Calibration using inverse propensity score weighting was applied to correct differences between POCOP and NCR. Results: The R-indicator of the entire POCOP registry was 0.72 95% confidence interval [0.71, 0.73]. Representativeness of palliative patients was higher than that of potentially curable patients (R-indicator 0.88 [0.85, 0.90] and 0.70 [0.68, 0.71], respectively). Stratification to clinically relevant subgroups based on treatment resulted in higher R-indicators of the respective subgroups. Both after stratification and calibration weighting survival estimates in the POCOP registry were more similar to that in the NCR population. Conclusion: This study demonstrated the assessment of real-world representativeness of patients who participated in a prospective registry cohort and showed that real-world representativeness improved when the variability in treatment was accounted for.</p

Assessing real-world representativeness of prospective registry cohorts in oncology:insights from patients with esophagogastric cancer

Objectives: This study aimed to explore the real-world representativeness of a prospective registry cohort with active accrual in oncology, applying a representativeness metric that is novel to health care. Study Design and Setting: We used data from the Prospective Observational Cohort Study of Esophageal-Gastric Cancer Patients (POCOP) registry and from the population-based Netherlands Cancer Registry (NCR). We used Representativeness-indicators (R-indicators) and overall survival to investigate the degree to which the POCOP cohort and clinically relevant subgroups were a representative sample compared to the NCR database. Calibration using inverse propensity score weighting was applied to correct differences between POCOP and NCR. Results: The R-indicator of the entire POCOP registry was 0.72 95% confidence interval [0.71, 0.73]. Representativeness of palliative patients was higher than that of potentially curable patients (R-indicator 0.88 [0.85, 0.90] and 0.70 [0.68, 0.71], respectively). Stratification to clinically relevant subgroups based on treatment resulted in higher R-indicators of the respective subgroups. Both after stratification and calibration weighting survival estimates in the POCOP registry were more similar to that in the NCR population. Conclusion: This study demonstrated the assessment of real-world representativeness of patients who participated in a prospective registry cohort and showed that real-world representativeness improved when the variability in treatment was accounted for.</p

Assessing real-world representativeness of prospective registry cohorts in oncology: insights from patients with esophagogastric cancer

OBJECTIVES: This study aimed to explore the real-world representativeness of a prospective registry cohort with active accrual in oncology, applying a representativeness metric that is novel to health care. STUDY DESIGN AND SETTING: We used data from the Prospective Observational Cohort Study of Esophageal-Gastric Cancer Patients (POCOP) registry and from the population-based Netherlands Cancer Registry (NCR). We used Representativeness-indicators (R-indicators) and overall survival to investigate the degree to which the POCOP cohort and clinically relevant subgroups were a representative sample compared to the NCR database. Calibration using inverse propensity score weighting was applied to correct differences between POCOP and NCR. RESULTS: The R-indicator of the entire POCOP registry was 0.72 95% confidence interval [0.71, 0.73]. Representativeness of palliative patients was higher than that of potentially curable patients (R-indicator 0.88 [0.85, 0.90] and 0.70 [0.68, 0.71], respectively). Stratification to clinically relevant subgroups based on treatment resulted in higher R-indicators of the respective subgroups. Both after stratification and calibration weighting survival estimates in the POCOP registry were more similar to that in the NCR population. CONCLUSION: This study demonstrated the assessment of real-world representativeness of patients who participated in a prospective registry cohort and showed that real-world representativeness improved when the variability in treatment was accounted for

What Works for Whom in School-Based Anti-bullying Interventions? An Individual Participant Data Meta-analysis

The prevalence of bullying worldwide is high (UNESCO, 2018). Over the past decades, many anti-bullying interventions have been developed to remediate this problem. However, we lack insight into for whom these interventions work and what individual intervention components drive the total intervention effects. We conducted a large-scale individual participant data (IPD) meta-analysis using data from 39,793 children and adolescents aged five to 20 years (Mage = 12.58, SD = 2.34) who had participated in quasi-experimental or randomized controlled trials of school-based anti-bullying interventions (i.e., 10 studies testing nine interventions). Multilevel logistic regression analyses showed that anti-bullying interventions significantly reduced self-reported victimization (d =  − 0.14) and bullying perpetration (d =  − 0.07). Anti-bullying interventions more strongly reduced bullying perpetration in younger participants (i.e., under age 12) and victimization for youth who were more heavily victimized before the intervention. We did not find evidence to show that the inclusion of specific intervention components was related to higher overall intervention effects, except for an iatrogenic effect of non-punitive disciplinary methods–which was strongest for girls. Exploratory analyses suggested that school assemblies and playground supervision may have harmful effects for some, increasing bullying perpetration in youth who already bullied frequently at baseline. In conclusion, school-based anti-bullying interventions are generally effective and work especially well for younger children and youth who are most heavily victimized. Further tailoring of interventions may be necessary to more effectively meet the needs and strengths of specific subgroups of children and adolescents. </p

Potential Adverse Outcomes of Shared Decision Making about Palliative Cancer Treatment: A Secondary Analysis of a Randomized Trial

Background: While shared decision making (SDM) is advocated for ethical reasons and beneficial outcomes, SDM might also negatively affect patients with incurable cancer. The current study explored whether SDM, and an oncologist training in SDM, are associated with adverse outcomes (i.e., patient anxiety, tension, helplessness/hopelessness, decisional uncertainty, and reduced fighting spirit). Design: A secondary analysis of a randomized clinical trial investigating the effects of SDM interventions in the context of advanced cancer. The relations between observed SDM (OPTION12), specific SDM elements (4SDM), oncologist SDM training, and adverse outcomes were analyzed. We modeled adverse outcomes as a multivariate phenomenon, followed by univariate regressions if significant. Results: In total, 194 patients consulted by 31 oncologists were included. In a multivariate analysis, observed SDM and adverse outcomes were significantly related. More specifically, more observed SDM in the consultation was related to patients reporting more tension (P = 0.002) and more decisional uncertainty (P = 0.004) at 1 wk after the consultation. The SDM element “informing about the options” was especially found to be related to adverse outcomes, specifically to more helplessness/hopelessness (P = 0.002) and more tension (P = 0.016) at 1 wk after the consultation. Whether the patient consulted an oncologist who had received SDM training or not was not significantly related to adverse outcomes. No relations with long-term adverse outcomes were found. Conclusions: It is important for oncologists to realize that for some patients, SDM may temporarily be associated with negative emotions. Further research is needed to untangle which, when, and how adverse outcomes might occur and whether and how burden may be minimized for patients. Observed shared decision making was related to more tension and uncertainty postconsultation in advanced cancer patients However, training oncologists in SDM did not affect adverse outcomes. Further research is needed to untangle which, when, and how adverse outcomes might occur and how burden may be minimized

Camtrap DP: an open standard for the FAIR exchange and archiving of camera trap data

Camera trapping has revolutionized wildlife ecology and conservation by providing automated data acquisition, leading to the accumulation of massive amounts of camera trap data worldwide. Although management and processing of camera trap-derived Big Data are becoming increasingly solvable with the help of scalable cyber-infrastructures, harmonization and exchange of the data remain limited, hindering its full potential. There is currently no widely accepted standard for exchanging camera trap data. The only existing proposal, “Camera Trap Metadata Standard” (CTMS), has several technical shortcomings and limited adoption. We present a new data exchange format, the Camera Trap Data Package (Camtrap DP), designed to allow users to easily exchange, harmonize and archive camera trap data at local to global scales. Camtrap DP structures camera trap data in a simple yet flexible data model consisting of three tables (Deployments, Media and Observations) that supports a wide range of camera deployment designs, classification techniques (e.g., human and AI, media-based and event-based) and analytical use cases, from compiling species occurrence data through distribution, occupancy and activity modeling to density estimation. The format further achieves interoperability by building upon existing standards, Frictionless Data Package in particular, which is supported by a suite of open software tools to read and validate data. Camtrap DP is the consensus of a long, in-depth, consultation and outreach process with standard and software developers, the main existing camera trap data management platforms, major players in the field of camera trapping and the Global Biodiversity Information Facility (GBIF). Under the umbrella of the Biodiversity Information Standards (TDWG), Camtrap DP has been developed openly, collaboratively and with version control from the start. We encourage camera trapping users and developers to join the discussion and contribute to the further development and adoption of this standar

Mammal responses to global changes in human activity vary by trophic group and landscape

Wildlife must adapt to human presence to survive in the Anthropocene, so it is critical to understand species responses to humans in different contexts. We used camera trapping as a lens to view mammal responses to changes in human activity during the COVID-19 pandemic. Across 163 species sampled in 102 projects around the world, changes in the amount and timing of animal activity varied widely. Under higher human activity, mammals were less active in undeveloped areas but unexpectedly more active in developed areas while exhibiting greater nocturnality. Carnivores were most sensitive, showing the strongest decreases in activity and greatest increases in nocturnality. Wildlife managers must consider how habituation and uneven sensitivity across species may cause fundamental differences in human–wildlife interactions along gradients of human influence.Peer reviewe

SOURCE beyond first-line: A survival prediction model for patients with metastatic esophagogastric adenocarcinoma after failure of first-line palliative systemic therapy

Prior models have been developed to predict survival for patients with esophagogastric cancer undergoing curative treatment or first-line chemotherapy (SOURCE models). Comprehensive clinical prediction models for patients with esophagogastric cancer who will receive second-line chemotherapy or best supportive care are currently lacking. The aim of our study was to develop and internally validate a new clinical prediction model, called SOURCE beyond first-line, for survival of patients with metastatic esophagogastric adenocarcinoma after failure of first-line palliative systemic therapy. Patients with unresectable or metastatic esophageal or gastric adenocarcinoma (2015-2017) who received first-line systemic therapy (N?=?1067) were selected from the Netherlands Cancer Registry. Patient, tumor and treatment characteristics at primary diagnosis and at progression of disease were used to develop the model. A Cox proportional hazards regression model was developed through forward and backward selection using Akaike's Information Criterion. The model was internally validated through 10-fold cross-validations to assess performance. Model discrimination (C-index) and calibration (slope and intercept) were used to evaluate performance of the complete and cross-validated models. The final model consisted of 11 patient tumor and treatment characteristics. The C-index was 0.75 (0.73-0.78), calibration slope 1.01 (1.00-1.01) and calibration intercept 0.01 (0.01-0.02). Internal cross-validation of the model showed that the model performed adequately on unseen data: C-index was 0.79 (0.77-0.82), calibration slope 0.93 (0.85-1.01) and calibration intercept 0.02 (-0.01 to 0.06). The SOURCE beyond first-line model predicted survival with fair discriminatory ability and good calibration

Beyond Median Overall Survival: Estimating Trends for Multiple Survival Scenarios in Patients With Metastatic Esophagogastric Cancer

Background: In recent years, clinical trials have shown improved survival of patients with metastatic esophageal or gastric cancer. The number of patients participating in clinical trials is limited, and survival improvements observed from clinical trials are unrepresentative for the full population. The aim of our study was to assess trends in survival for the best-case, typical, and worst-case scenarios in patients with metastatic esophageal or gastric cancer. Methods: We selected patients with metastatic esophageal or gastric cancer diagnosed between 2006 and 2020 fromthe nationwideNetherlands Cancer Registry. Survival was calculated for different percentiles of the survival curve for each incidence year (eg, the 10th percentile [p10] represents the top 10% of patients with the best survival): p10 (best-case), p25 (upper-typical), p50 (median), p75 (lower-typical), and p90 (worstcase). Weighted linear regression analyses were performed to test whether changes in survival were significant. Results: The overall median survival between 2006 and 2020 remained unchanged for patients with esophageal cancer (n510,448; from 5.2 to 5.2 months, respectively; P5.06) and improved for patients with gastric cancer (n510,512; from 3.5 to 4.3 months, respectively; P5.001). For patients with esophageal cancer, survival for the best-case scenario (p10; best 10% of patients) significantly improved from 17.2 to 21.0 months (P5.006). For patients with gastric cancer, survival significantly improved for the best-case scenario (p10) from 15.9 to 23.5 months (P,.001) and the upper-typical scenario (p25) scenario improved from 7.9 to 9.9 months (P,.001). Conclusions: Despite significant survival improvements in clinical trials, survival improvements were not observed for the majority of patients treated in daily clinical practice. An increase in survival was only observed for patients with the best prognosis