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

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

Conditional relative survival in nonmetastatic esophagogastric cancer between 2006 and 2020: A population-based study

Conditional relative survival (CRS) is useful for communicating prognosis to patients as it provides an estimate of the life expectancy after having survived a certain time after treatment. Our study estimates the 3-year relative survival conditional on having survived a certain period for patients with esophageal or gastric cancer. Patients with nonmetastatic esophageal or gastric cancer diagnosed between 2006 and 2020 treated with curative intent (resection with or without [neo]adjuvant therapy, or chemoradiotherapy) were selected from the Netherlands Cancer Registry. CRS was calculated since resection or last day of chemoradiotherapy. The probability of surviving an additional 3 years (ie, 3-year CRS), if the patients survived 1, 3 and 5 years after diagnosis was 62%, 79%, 87% and 69%, 84%, 90% for esophageal and gastric cancer, respectively. The 3-year CRS after having survived 3 years for patients with esophageal cancer who underwent a resection (n = 12 204) was 91%, 88%, 77% and 60% for pathological Stage 0, I, II and III, and for patients with esophageal cancer who received chemoradiotherapy (n = 4158) was 51% and 66% for clinical Stage II and III, respectively. The 3-year CRS after having survived 3 years for patients with gastric cancer who underwent a resection (n = 6531) was 99%, 90%, 73% and 59% for pathological Stage 0, I, II and III, respectively. Despite poor prognosis of patients with esophageal or gastric cancer, life expectancy increases substantially after patients have survived several years after treatment. Our study provides valuable information for communication of prognosis to patients during follow-up after treatment

Improving survival prediction of oesophageal cancer patients treated with external beam radiotherapy for dysphagia

Introduction: The recent POLDER trial investigated the effects of external beam radiotherapy (EBRT) on dysphagia caused by incurable oesophageal cancer. An estimated life expectancy of minimally three months was required for inclusion. However, nearly one-third of the included patients died within three months. The aim of this study was to investigate if the use of prediction models could have improved the physician’s estimation of the patient’s survival. Methods: Data from the POLDER trial (N = 110) were linked to the Netherlands Cancer Registry to retrieve patient, tumour, and treatment characteristics. Two published prediction models (the SOURCE model and Steyerberg model) were used to predict three-month survival for all patients included in the POLDER trial. Predicted survival probabilities were dichotomised and the accuracy, sensitivity, specificity, and the area under the curve (AUC) were used to evaluate the predictive performance. Results: The SOURCE and Steyerberg model had an accuracy of 79% and 64%, and an AUC of 0.76 and 0.60 (p =.017), respectively. The SOURCE model had higher specificity across survival cut-off probabilities, the Steyerberg model had a higher sensitivity beyond the survival probability cut-off of 0.7. Using optimal cut-off probabilities, SOURCE would have wrongfully included 16/110 patients into the POLDER and Steyerberg 34/110. Conclusion: The SOURCE model was found to be a more useful decision aid than the Steyerberg model. Results showed that the SOURCE model could be used for three-month survival predictions for patients that are considered for palliative treatment of dysphagia caused by oesophageal cancer in addition to clinicians’ judgement

Trends in best-case, typical and worst-case survival scenarios of patients with non-metastatic esophagogastric cancer between 2006 and 2020: A population-based study

New treatment options and centralization of surgery have improved survival for patients with non-metastatic esophageal or gastric cancer. It is unknown, however, which patients benefitted the most from treatment advances. The aim of this study was to identify best-case, typical and worst-case scenarios in terms of survival time, and to assess if survival associated with these scenarios changed over time. Patients with non-metastatic potentially resectable esophageal or gastric cancer diagnosed between 2006 and 2020 were selected from the Netherlands Cancer Registry. Best-case (20th percentile), upper-typical (40th percentile), typical (median), lower-typical (60th percentile) and worst-case (80th percentile) survival scenarios were defined, and regression analysis was used to investigate the change in survival time for each scenario across years. For patients with esophageal cancer (N = 24 352) survival time improved on average 12.0 (until 2011), 1.5 (until 2018), 0.7, 0.4 and 0.2 months per year for the best-case, upper-typical, median, lower-typical and worst-case scenario, respectively. For patients with gastric cancer (N = 9993) survival time of the best-case scenario remained constant, whereas the upper-typical, median, lower-typical and worst-case scenario improved on average with 1.0 (until 2018), 0.5, 0.2 and 0.2 months per year, respectively. Subgroup analyses showed that, survival scenarios improved for nearly all patients across treatment groups and for patients with squamous cell carcinomas or adenocarcinomas. Survival improved for almost all patients suggesting that in clinical practice the vast majority of patients benefitted from treatment advances. The clinically most meaningful survival advantage was observed for the best-case scenario of esophageal cancer

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

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

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