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Abstract Background The Interrupted Time Series (ITS) is a robust design for evaluating public health and policy interventions or exposures when randomisation may be infeasible. Several statistical methods are available for the analysis and meta-analysis of ITS studies. We sought to empirically compare available methods when applied to real-world ITS data. Methods We sourced ITS data from published meta-analyses to create an online data repository. Each dataset was re-analysed using two ITS estimation methods. The level- and slope-change effect estimates (and standard errors) were calculated and combined using fixed-effect and four random-effects meta-analysis methods. We examined differences in meta-analytic level- and slope-change estimates, their 95% confidence intervals, p-values, and estimates of heterogeneity across the statistical methods. Results Of 40 eligible meta-analyses, data from 17 meta-analyses including 282 ITS studies were obtained (predominantly investigating the effects of public health interruptions (88%)) and analysed. We found that on average, the meta-analytic effect estimates, their standard errors and between-study variances were not sensitive to meta-analysis method choice, irrespective of the ITS analysis method. However, across ITS analysis methods, for any given meta-analysis, there could be small to moderate differences in meta-analytic effect estimates, and important differences in the meta-analytic standard errors. Furthermore, the confidence interval widths and p-values for the meta-analytic effect estimates varied depending on the choice of confidence interval method and ITS analysis method. Conclusions Our empirical study showed that meta-analysis effect estimates, their standard errors, confidence interval widths and p-values can be affected by statistical method choice. These differences may importantly impact interpretations and conclusions of a meta-analysis and suggest that the statistical methods are not interchangeable in practice.

Abstract Objective Primary care practitioners are crucial to engaging people in Australia's national cervical screening program. From July 2022, practitioners have been able to offer all screen‐eligible people the choice to collect their own self‐collected sample; an option introduced to increase equity. This study explored how practitioners are intending to incorporate universal access to self‐collection into their clinical care. Methods Semi‐structed interviews with 27 general practitioners, nurses, and practice managers from 10 practices in Victoria, Australia conducted between May and August 2022. Interviews were deductively coded, informed by the Consolidated Framework for Implementation Research. The Diffusion of Innovations theory was used to categorise intention to provide self‐collection. Results Participants were supportive of universal access to self‐collection, citing benefits for screen‐eligible people and that it overcame the limited adaptability of the previous policy. Most participants' practices (n = 7, 70%) had implemented or had plans to offer the option for self‐collection to all. Participants deliberating whether to provide universal access to self‐collection held concerns about the correct performance of the self‐test and the perceived loss of opportunity to perform a pelvic examination. Limited time to change practice‐level processes and competing demands within consultations were anticipated as implementation barriers. Conclusions The extent to which self‐collection can promote equity within the program will be limited without wide‐spread adoption by practitioners. Communication and education that addresses concerns of practitioners, along with targeted implementation support, will be critical to ensuring that self‐collection can increase participation and Australia's progression towards elimination of cervical cancer.

Abstract Background Identifying risk factors for metachronous colorectal cancer (CRC) and metachronous advanced neoplasia could be useful for guiding surveillance. We conducted a systematic review and meta-analysis to investigate risk factors for metachronous CRC and advanced neoplasia. Methods Searches were conducted in MEDLINE, Embase, Web of Science and Cochrane Central Registry of Controlled Trials for articles (searching period: 1945 to Feburary, 2021) that reported the results of an association between any factor and metachronous advanced neoplasia or metachronous CRC. There were no restrictions on the publication date or language. Random effects models were fitted to estimate the combined association between the risk factors and metachronous CRC or advanced neoplasia. The Risk of Bias In Non-Randomised Studies of Interventions tool (ROBINS-I) was used to assess the risk of bias of included studies. Results In total, 22 observational studies with 625,208 participants were included in the systematic review and meta-analysis. Of these, 13 studies investigated risk factors for metachronous CRC and 9 for advanced neoplasia. The risks of metachronous CRC or advanced neoplasia were higher if the first CRC was diagnosed in the presence of a synchronous advanced lesion (pooled risk ratio (RR) from 3 studies: 3.61, 95% confidence interval (CI): 1.44–9.05; and pooled RR from 8 studies: 2.77, 95% CI: 2.23–3.43, respectively). The risk of metachronous CRC was lower, but the risk of metachronous advanced neoplasia was higher if the first CRC was distal (compared with proximal) (pooled RR from 3 studies: 0.48, 95% CI: 0.23–0.98; and pooled RR from 2 studies: 2.99, 95% CI: 1.60–5.58 respectively). The risk of metachronous advanced neoplasia increased with age (pooled RR from 3 studies: 1.07 per year of age, 95% CI: 1.03–1.11). There was no evidence that any lifestyle risk factors studied were associated with the risk of metachronous CRC or advanced neoplasia. Conclusions The identified risk factors for metachronous CRC and advanced neoplasia might be useful to tailor the existing surveillance guidelines after the first CRC. There were potential limitations due to possible misclassification of the outcome, confounding and risk of bias, and the findings cannot be generalised to high-risk genetic syndrome cases.

Interrupted time series (ITS) are often meta-analysed to inform public health and policy decisions but examination of the statistical methods for ITS analysis and meta-analysis in this context is limited. We simulated meta-analyses of ITS studies with continuous outcome data, analysed the studies using segmented linear regression with two estimation methods [ordinary least squares (OLS) and restricted maximum likelihood (REML)], and meta-analysed the immediate level- and slope-change effect estimates using fixed-effect and (multiple) random-effects meta-analysis methods. Simulation design parameters included varying series length; magnitude of lag-1 autocorrelation; magnitude of level- and slope-changes; number of included studies; and, effect size heterogeneity. All meta-analysis methods yielded unbiased estimates of the interruption effects. All random effects meta-analysis methods yielded coverage close to the nominal level, irrespective of the ITS analysis method used and other design parameters. However, heterogeneity was frequently overestimated in scenarios where the ITS study standard errors were underestimated, which occurred for short series or when the ITS analysis method did not appropriately account for autocorrelation. The performance of meta-analysis methods depends on the design and analysis of the included ITS studies. Although all random effects methods performed well in terms of coverage, irrespective of the ITS analysis method, we recommend the use of effect estimates calculated from ITS methods that adjust for autocorrelation when possible. Doing so will likely to lead to more accurate estimates of the heterogeneity variance.

BackgroundMechanisms underlying the adiposity-cancer relationship are incompletely understood. We quantified the mediating roles of C-reactive protein (CRP), leptin, fasting insulin, and estradiol in the effect of adiposity on estrogen receptor (ER)-positive breast, endometrial, and colorectal cancer risk in postmenopausal women.MethodsWe used a case-cohort study within the Women's Health Initiative Observational Study, analyzed as a cumulative sampling case-control study. The study included 188 breast cancer cases, 98 endometrial cancer cases, 193 colorectal cancer cases, and 285 controls. Interventional indirect and direct effects on the risk ratio (RR) scale were estimated using causal mediation analysis.ResultsFor breast cancer, the total effect RR for BMI ≥30 versus ≥18.5-

Abstract Background Quantifying the benefits and harms of breast cancer screening accurately is important for planning and evaluating screening programs and for enabling women to make informed decisions about participation. However, few cohort studies have attempted to estimate benefit and harm simultaneously. Aims We aimed to quantify the impact of mammographic screening on breast cancer mortality and overdiagnosis using a cohort of women invited to attend Australia's national screening program, BreastScreen. Methods In a cohort of 41,330 women without prior breast cancer diagnosis, screening, or diagnostic procedures invited to attend BreastScreen Western Australia in 1994‐1995, we estimated the cumulative risk of breast cancer mortality and breast cancer incidence (invasive and ductal carcinoma in situ) from age 50 to 85 years for attenders and non‐attenders. Data were obtained by linking population‐based state and national health registries. Breast cancer mortality risks were estimated from a survival analysis that accounted for competing risk of death from other causes. Breast cancer risk for unscreened women was estimated by survival analysis, while accounting for competing causes of death. For screened women, breast cancer risk was the sum of risk of being diagnosed at first screen, estimated using logistic regression, and risk of diagnosis following a negative first screen estimated from a survival analysis. Results For every 1,000 women 50 years old at first invitation to attend BreastScreen, there were 20 (95% CI 12‐30) fewer breast cancer deaths and 25 (95% CI 15‐35) more breast cancers diagnosed for women who attended than for non‐attendees by age 85. Of the breast cancers diagnosed in screened women, 21% (95% CI 13%‐27%) could be attributed to screening. Discussion The estimated ratio of benefit to harm was consistent with, but slightly less favourable to screening than most other estimates from cohort studies. Conclusion Women who participate in organised screening for breast cancer in Australia have substantially lower breast cancer mortality, while some screen‐detected cancers may be overdiagnosed.

Abstract Background Retaining participants in cohort studies with multiple follow-up waves is difficult. Commonly, researchers are faced with the problem of missing data, which may introduce biased results as well as a loss of statistical power and precision. The STROBE guidelines von Elm et al. (Lancet, 370:1453-1457, 2007); Vandenbroucke et al. (PLoS Med, 4:e297, 2007) and the guidelines proposed by Sterne et al. (BMJ, 338:b2393, 2009) recommend that cohort studies report on the amount of missing data, the reasons for non-participation and non-response, and the method used to handle missing data in the analyses. We have conducted a review of publications from cohort studies in order to document the reporting of missing data for exposure measures and to describe the statistical methods used to account for the missing data. Methods A systematic search of English language papers published from January 2000 to December 2009 was carried out in PubMed. Prospective cohort studies with a sample size greater than 1,000 that analysed data using repeated measures of exposure were included. Results Among the 82 papers meeting the inclusion criteria, only 35 (43%) reported the amount of missing data according to the suggested guidelines. Sixty-eight papers (83%) described how they dealt with missing data in the analysis. Most of the papers excluded participants with missing data and performed a complete-case analysis (n = 54, 66%). Other papers used more sophisticated methods including multiple imputation (n = 5) or fully Bayesian modeling (n = 1). Methods known to produce biased results were also used, for example, Last Observation Carried Forward (n = 7), the missing indicator method (n = 1), and mean value substitution (n = 3). For the remaining 14 papers, the method used to handle missing data in the analysis was not stated. Conclusions This review highlights the inconsistent reporting of missing data in cohort studies and the continuing use of inappropriate methods to handle missing data in the analysis. Epidemiological journals should invoke the STROBE guidelines as a framework for authors so that the amount of missing data and how this was accounted for in the analysis is transparent in the reporting of cohort studies.

Exploratory data analysis is a crucial part of data-driven scientific discovery. Yet, the process of discovering insights from visualization can be a manual and painstaking process. This article discusses some of the lessons we learned from working with scientists in designing visual data exploration system, along with design considerations for future tools.

Visual query systems (VQSs) empower users to interactively search for line charts with desired visual patterns, typically specified using intuitive sketch-based interfaces. Despite decades of past work on VQSs, these efforts have not translated to adoption in practice, possibly because VQSs are largely evaluated in unrealistic lab-based settings. To remedy this gap in adoption, we collaborated with experts from three diverse domains-astronomy, genetics, and material science-via a year-long user-centered design process to develop a VQS that supports their workflow and analytical needs, and evaluate how VQSs can be used in practice. Our study results reveal that ad-hoc sketch-only querying is not as commonly used as prior work suggests, since analysts are often unable to precisely express their patterns of interest. In addition, we characterize three essential sensemaking processes supported by our enhanced VQS. We discover that participants employ all three processes, but in different proportions, depending on the analytical needs in each domain. Our findings suggest that all three sensemaking processes must be integrated in order to make future VQSs useful for a wide range of analytical inquiries.