Differences between arm‐based (AB) and contrast‐based (CB) models for network meta‐analysis (NMA) are controversial. We compare the CB model of Lu and Ades (2006), the AB model of Hong et al(2016), ...and two intermediate models, using hypothetical data and a selected real data set. Differences between models arise primarily from study intercepts being fixed effects in the Lu‐Ades model but random effects in the Hong model, and we identify four key difference. (1) If study intercepts are fixed effects then only within‐study information is used, but if they are random effects then between‐study information is also used and can cause important bias. (2) Models with random study intercepts are suitable for deriving a wider range of estimands, eg, the marginal risk difference, when underlying risk is derived from the NMA data; but underlying risk is usually best derived from external data, and then models with fixed intercepts are equally good. (3) The Hong model allows treatment effects to be related to study intercepts, but the Lu‐Ades model does not. (4) The Hong model is valid under a more relaxed missing data assumption, that arms (rather than contrasts) are missing at random, but this does not appear to reduce bias. We also describe an AB model with fixed study intercepts and a CB model with random study intercepts. We conclude that both AB and CB models are suitable for the analysis of NMA data, but using random study intercepts requires a strong rationale such as relating treatment effects to study intercepts.
Non-melanoma skin cancer in Australia FRANSEN, Marloes; KARAHALIOS, Amalia; SHARMA, Niyati ...
Medical journal of Australia,
11/2012, Volume:
197, Issue:
10
Journal Article
Peer reviewed
Open access
To report the burden and cost of non-melanoma skin cancer (NMSC) treatments in Australia and to project estimates of numbers and costs to 2015.
Retrospective study of data obtained from Medicare ...Australia for NMSC treated by excision, curettage, laser or cryotherapy between 1 January 1997 and 31 December 2010, by year, sex, age group and state or territory.
Total number, total Medicare Benefits Schedule (MBS) benefit and total cost in Australian dollars of NMSC treatments.
The total number of NMSC treatments increased from 412 493 in 1997 to 767 347 in 2010, and we estimated that the number of treatments would increase to 938 991 (95% CI, 901 047-976 934) by 2015. The total MBS benefit for NMSC treatments in 2010 was $93.5 million, and we estimated that this will increase to $109.8 million (95% CI, $105.9-$113.7 million) by 2015, whereas the total cost with inflation (ie, cost which includes diagnosis, treatment and pathology) was $511.0 million in 2010, estimated to increase to $703.0 million (95% CI, $674.6-$731.4 million) by 2015.
NMSC treatments increased by 86% between 1997 and 2010. We anticipate that the number and the total cost without inflation of NMSC treatments will increase by a further 22% between 2010 and 2015. NMSC will remain the most costly cancer and place an increasing burden on the Australian health care system.
Interrupted time series (ITS) designs are frequently used in public health to examine whether an intervention or exposure has influenced health outcomes. Few reviews have been undertaken to examine ...the design characteristics, statistical methods, and completeness of reporting of published ITS studies.
We used stratified random sampling to identify 200 ITS studies that evaluated public health interventions or exposures from PubMed (2013–2017). Study characteristics, details of statistical models and estimation methods used, effect metrics, and parameter estimates were extracted. From the 200 studies, 230 time series were examined.
Common statistical methods used were linear regression (31%, 72/230) and autoregressive integrated moving average (19%, 43/230). In 17% (40/230) of the series, we could not determine the statistical method used. Autocorrelation was acknowledged in 63% (145/230) of the series. An estimate of the autocorrelation coefficient was given for only 1% of the series (3/230). Measures of precision were reported for 63% of effect measures (541/852).
Many aspects of the design, methods, analysis, and reporting of ITS studies can be improved, particularly description of the statistical methods and approaches to adjust for and estimate autocorrelation. More guidance on the conduct and reporting of ITS studies is needed to improve this study design.
Interrupted time series (ITS) studies are frequently used to evaluate the effects of population-level interventions or exposures. However, examination of the performance of statistical methods for ...this design has received relatively little attention.
We simulated continuous data to compare the performance of a set of statistical methods under a range of scenarios which included different level and slope changes, varying lengths of series and magnitudes of lag-1 autocorrelation. We also examined the performance of the Durbin-Watson (DW) test for detecting autocorrelation.
All methods yielded unbiased estimates of the level and slope changes over all scenarios. The magnitude of autocorrelation was underestimated by all methods, however, restricted maximum likelihood (REML) yielded the least biased estimates. Underestimation of autocorrelation led to standard errors that were too small and coverage less than the nominal 95%. All methods performed better with longer time series, except for ordinary least squares (OLS) in the presence of autocorrelation and Newey-West for high values of autocorrelation. The DW test for the presence of autocorrelation performed poorly except for long series and large autocorrelation.
From the methods evaluated, OLS was the preferred method in series with fewer than 12 points, while in longer series, REML was preferred. The DW test should not be relied upon to detect autocorrelation, except when the series is long. Care is needed when interpreting results from all methods, given confidence intervals will generally be too narrow. Further research is required to develop better performing methods for ITS, especially for short series.
The Interrupted Time Series (ITS) is a quasi-experimental design commonly used in public health to evaluate the impact of interventions or exposures. Multiple statistical methods are available to ...analyse data from ITS studies, but no empirical investigation has examined how the different methods compare when applied to real-world datasets.
A random sample of 200 ITS studies identified in a previous methods review were included. Time series data from each of these studies was sought. Each dataset was re-analysed using six statistical methods. Point and confidence interval estimates for level and slope changes, standard errors, p-values and estimates of autocorrelation were compared between methods.
From the 200 ITS studies, including 230 time series, 190 datasets were obtained. We found that the choice of statistical method can importantly affect the level and slope change point estimates, their standard errors, width of confidence intervals and p-values. Statistical significance (categorised at the 5% level) often differed across the pairwise comparisons of methods, ranging from 4 to 25% disagreement. Estimates of autocorrelation differed depending on the method used and the length of the series.
The choice of statistical method in ITS studies can lead to substantially different conclusions about the impact of the interruption. Pre-specification of the statistical method is encouraged, and naive conclusions based on statistical significance should be avoided.
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.
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.
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.
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.
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.
Mandatory prospective trial registration was introduced in 2005 to reduce publication bias and selective outcome reporting. In this study, we measured the proportion of prospective trial registration ...in randomized controlled trials in the anesthesia literature after this introduction, discrepancies between these trial protocols and subsequent publications, the association between being prospectively registered and reporting positive or negative results, and between being prospectively registered and achieving publication. We reviewed all abstracts from the American Society of Anesthesiologists annual meetings between 2010–2016 and included randomized controlled trials in humans. The abstract conclusions were scored as positive or negative according to predetermined definitions. We conducted a systematic search for trial registration and subsequent publication. Of the 9789 abstracts reviewed, 1070 abstracts were included. 222 (21%) of these abstracts had undergone prospective trial registration. 168/222 (76%) had a corresponding journal publication. 81(48%) had a major discrepancy between registration and publication. 149 (67%) of the abstracts with registration had positive outcomes compared with 616 (73%) of those without (Odds Ratio 0.77; 95% CI: 0.56 to 1.06; P = 0.105). Abstracts that had been registered were more likely to proceed to publication than those that had not (Odds Ratio 3.82; 95% CI 2.73 to 5.35; P < 0.001). The proportion of randomized controlled trials being prospectively registered in anesthesia remains low. Discrepancies between registry entries and corresponding journal publications are common. There was no association between prospective trial registration and subsequent positive outcomes. There was a strong association between prospective trial registration and the likelihood of progression to journal publication.
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.
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.
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.
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.
Purpose
Previous studies have shown that acquiring a disability is associated with a reduction in mental health, but they have not considered the cumulative impact of having a disability on mental ...health. We used acquisition of a non-psychological disability to estimate the association of each additional year lived with disability on mental health (measured using the Mental Component Summary score of the Short Form Health Survey).
Methods
We used the first 13 waves of data (years 2001–2013) from the Household, Income and Labour Dynamics in Australia Survey. The sample included 4113 working-age (18–65 years) adults who were disability-free at waves 1 and 2. We fitted marginal structural models with inverse probability weights to estimate the association of each additional year of living with disability on mental health, employing multiple imputation to handle the missing data.
Results
Of the 4113 participants, 7.7 percent acquired a disability. On average, each additional year lived with disability was associated with a decrease in the mean Mental Component Summary score (
β
= − 0.42; 95% CI − 0.71, − 0.14).
Conclusions
This study provides evidence that each additional year lived with non-psychological disability is associated with a decline in mental health among working-age Australians.
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