1,722,783 research outputs found
Combining estimates of interest in prognostic modelling studies after multiple imputation: current practice and guidelines
Full text linkBackground: Multiple imputation (MI) provides an effective approach to handle missing covariate
data within prognostic modelling studies, as it can properly account for the missing data
uncertainty. The multiply imputed datasets are each analysed using standard prognostic modelling
techniques to obtain the estimates of interest. The estimates from each imputed dataset are then
combined into one overall estimate and variance, incorporating both the within and between
imputation variability. Rubin's rules for combining these multiply imputed estimates are based on
asymptotic theory. The resulting combined estimates may be more accurate if the posterior
distribution of the population parameter of interest is better approximated by the normal
distribution. However, the normality assumption may not be appropriate for all the parameters of
interest when analysing prognostic modelling studies, such as predicted survival probabilities and
model performance measures.
Methods: Guidelines for combining the estimates of interest when analysing prognostic modelling
studies are provided. A literature review is performed to identify current practice for combining
such estimates in prognostic modelling studies.
Results: Methods for combining all reported estimates after MI were not well reported in the
current literature. Rubin's rules without applying any transformations were the standard approach
used, when any method was stated.
Conclusion: The proposed simple guidelines for combining estimates after MI may lead to a wider
and more appropriate use of MI in future prognostic modelling studies
Estimating excess hazard ratios and net survival when covariate data are missing: strategies for multiple imputation.
No full textBACKGROUND: Net survival is the survival probability we would observe if the disease under study were the only cause of death. When estimated from routinely collected population-based cancer registry data, this indicator is a key metric for cancer control. Unfortunately, such data typically contain a non-negligible proportion of missing values on important prognostic factors (eg, tumor stage). METHODS: We carried out an empirical study to compare the performance of complete records analysis and several multiple imputation strategies when net survival is estimated via a flexible parametric proportional hazards model that includes stage, a partially observed categorical covariate. Starting from fully observed cancer registry data, we induced missingness on stage under three scenarios. For each of these scenarios, we simulated 100 incomplete datasets and evaluated the performance of the different strategies. RESULTS: Ordinal logistic models are not suitable for the imputation of tumor stage. Complete records analysis may lead to grossly misleading estimates of net survival, even when the missing data mechanism is conditionally independent of survival time given the covariates and the bias on the excess hazard ratios estimates is negligible. CONCLUSIONS: As key covariates are unlikely missing completely at random, studies estimating net survival should not use complete records. When the missingness can be inferred from available data, appropriate multiple imputation should be performed. In the context of flexible parametric proportional hazards models with a partially observed stage covariate, a multinomial logistic imputation model for stage should be used and should include the Nelson-Aalen cumulative hazard estimate and the event indicator
The relationship between quality of research and citation frequency.
Full text linkBACKGROUND: Citation counts are often regarded as a measure of the utilization and contribution of published articles. The objective of this study is to assess whether statistical reporting and statistical errors in the analysis of the primary outcome are associated with the number of citations received. METHODS: We evaluated all original research articles published in 1996 in four psychiatric journals. The statistical and reporting quality of each paper was assessed and the number of citations received up to 2005 was obtained from the Web of Science database. We then examined whether the number of citations was associated with the quality of the statistical analysis and reporting. RESULTS: A total of 448 research papers were included in the citation analysis. Unclear or inadequate reporting of the research question and primary outcome were not statistically significantly associated with the citation counts. After adjusting for journal, extended description of statistical procedures had a positive effect on the number of citations received. Inappropriate statistical analysis did not affect the number of citations received. Adequate reporting of the primary research question, statistical methods and primary findings were all associated with the journal visibility and prestige. CONCLUSION: In this cohort of published research, measures of reporting quality and appropriate statistical analysis were not associated with the number of citations. The journal in which a study is published appears to be as important as the statistical reporting quality in ensuring dissemination of published medical science
The effect of patients’ preference on outcome in the EVerT cryotherapy versus salicylic acid for the treatment of plantar warts (verruca) trial
Full text linkBackground
Randomised controlled trials are widely accepted as the gold standard method to evaluate medical interventions, but they are still open to bias. One such bias is the effect of patient’s preference on outcome measures. The aims of this study were to examine whether patients’ treatment preference affected clearance of plantar warts and explore whether there were any associations between patients’ treatment preference and baseline variables in the EverT trial.
Methods
Two hundred and forty patients were recruited from University podiatry schools, NHS podiatry clinics and primary care. Patients were aged 12 years and over and had at least one plantar wart which was suitable for treatment with salicylic acid and cryotherapy. Patients were asked their treatment preference prior to randomisation. The Kruskal-Wallis test was performed to test the association between preference group and continuous baseline variables. The Fisher’s exact test was performed to test the association between preference group and categorical baseline variables. A logistic regression analysis was undertaken with verruca clearance (yes or no) as the dependent variable and treatment, age, type of verruca, previous treatment, treatment preference as independent variables. Two analyses were undertaken, one using the health professional reported outcome and one using the patient’s self reported outcomes. Data on whether the patient found it necessary to stop the treatment to which they had been allocated and whether they started another treatment were summarised by treatment group.
Results
Pre-randomisation preferences were: 10% for salicylic acid; 42% for cryotherapy and 48% no treatment preference. There was no evidence of an association between treatment preference group and either patient (p=0.95) or healthcare professional (p=0.46) reported verruca clearance rates. There was no evidence of an association between preference group and any of the baseline variables except gender, with more females expressing a preference for salicylic acid (p=0.004). There was no evidence that the number of times salicylic acid was applied was different between the preference groups at one week (p=0.89) or at three weeks (p=0.24). Similarly, for the number of clinic visits for cryotherapy (p=0.71)
Conclusions
This secondary analysis showed no evidence to suggest that patients’ baseline preferences affected verruca clearance rates or adherence with the treatment
CONSORT for Reporting Randomized Controlled Trials in Journal and Conference Abstracts: Explanation and Elaboration
Full text linkBACKGROUND: Clear, transparent, and sufficiently detailed abstracts of conferences and journal articles related to randomized controlled trials (RCTs) are important, because readers often base their assessment of a trial solely on information in the abstract. Here, we extend the CONSORT (Consolidated Standards of Reporting Trials) Statement to develop a minimum list of essential items, which authors should consider when reporting the results of a RCT in any journal or conference abstract. METHODS AND FINDINGS: We generated a list of items from existing quality assessment tools and empirical evidence. A three-round, modified-Delphi process was used to select items. In all, 109 participants were invited to participate in an electronic survey; the response rate was 61%. Survey results were presented at a meeting of the CONSORT Group in Montebello, Canada, January 2007, involving 26 participants, including clinical trialists, statisticians, epidemiologists, and biomedical editors. Checklist items were discussed for eligibility into the final checklist. The checklist was then revised to ensure that it reflected discussions held during and subsequent to the meeting. CONSORT for Abstracts recommends that abstracts relating to RCTs have a structured format. Items should include details of trial objectives; trial design (e.g., method of allocation, blinding/masking); trial participants (i.e., description, numbers randomized, and number analyzed); interventions intended for each randomized group and their impact on primary efficacy outcomes and harms; trial conclusions; trial registration name and number; and source of funding. We recommend the checklist be used in conjunction with this explanatory document, which includes examples of good reporting, rationale, and evidence, when available, for the inclusion of each item. CONCLUSIONS: CONSORT for Abstracts aims to improve reporting of abstracts of RCTs published in journal articles and conference proceedings. It will help authors of abstracts of these trials provide the detail and clarity needed by readers wishing to assess a trial's validity and the applicability of its results.Sally Hopewell, Mike Clarke, David Moher, Elizabeth Wager, Philippa Middleton, Douglas G. Altman, Kenneth F. Schulz, and the CONSORT Grou
Evaluation of the Indian Migration Study Physical Activity Questionnaire (IMS-PAQ): a cross-sectional study.
Full text linkABSTRACT:
Socio-cultural differences for country-specific activities are rarely addressed in physical activity questionnaires. We examined the reliability and validity of the Indian Migration Study Physical Activity Questionnaire (IMS-PAQ) in urban and rural groups in India.
A sub-sample of IMS participants (n = 479) was used to examine short term (≤1 month [n = 158]) and long term (> 1 month [n = 321]) IMS-PAQ reliability for levels of total, sedentary, light and moderate/vigorous activity (MVPA) intensity using intraclass correlation (ICC) and kappa coefficients (k). Criterion validity (n = 157) was examined by comparing the IMS-PAQ to a uniaxial accelerometer (ACC) worn ≥4 days, via Spearman's rank correlations (ρ) and k, using Bland-Altman plots to check for systematic bias. Construct validity (n = 7,000) was established using linear regression, comparing IMS-PAQ against theoretical constructs associated with physical activity (PA): BMI [kg/m2], percent body fat and pulse rate.
IMS-PAQ reliability ranged from ICC 0.42-0.88 and k = 0.37-0.61 (≤1 month) and ICC 0.26 to 0.62; kappa 0.17 to 0.45 (> 1 month). Criterion validity was ρ = 0.18-0.48; k = 0.08-0.34. Light activity was underestimated and MVPA consistently and substantially overestimated for the IMS-PAQ vs. the accelerometer. Criterion validity was moderate for total activity and MVPA. Reliability and validity were comparable for urban and rural participants but lower in women than men. Increasing time spent in total activity or MVPA, and decreasing time in sedentary activity were associated with decreasing BMI, percent body fat and pulse rate, thereby demonstrating construct validity.
IMS-PAQ reliability and validity is similar to comparable self-reported instruments. It is an appropriate tool for ranking PA of individuals in India. Some refinements may be required for sedentary populations and women in India
The importance of allocation concealment and patient blinding in osteoarthritis trials: a meta-epidemiologic study
No full textOBJECTIVE: To evaluate the association of adequate allocation concealment and
patient blinding with estimates of treatment benefits in osteoarthritis trials.
METHODS: We performed a meta-epidemiologic study of 16 meta-analyses with 175
trials that compared therapeutic interventions with placebo or nonintervention
control in patients with hip or knee osteoarthritis. We calculated effect sizes
from the differences in means of pain intensity between groups at the end of
followup divided by the pooled SD and compared effect sizes between trials with
and trials without adequate methodology.
RESULTS: Effect sizes tended to be less beneficial in 46 trials with adequate
allocation concealment compared with 112 trials with inadequate or unclear
concealment of allocation (difference -0.15; 95% confidence interval [95% CI]
-0.31, 0.02). Selection bias associated with inadequate or unclear concealment of
allocation was most pronounced in meta-analyses with large estimated treatment
benefits (P for interaction < 0.001), meta-analyses with high between-trial
heterogeneity (P = 0.009), and meta-analyses of complementary medicine (P =
0.019). Effect sizes tended to be less beneficial in 64 trials with adequate
blinding of patients compared with 58 trials without (difference -0.15; 95% CI
-0.39, 0.09), but differences were less consistent and disappeared after
accounting for allocation concealment. Detection bias associated with a lack of
adequate patient blinding was most pronounced for nonpharmacologic interventions
(P for interaction < 0.001).
CONCLUSION: Results of osteoarthritis trials may be affected by selection and
detection bias. Adequate concealment of allocation and attempts to blind patients
will minimize these biases
Uses and misuses of the STROBE statement: bibliographic study
Full text linkObjectives Appropriate reporting is central to the application of findings from
research to clinical practice. The Strengthening the Reporting of Observational
Studies in Epidemiology (STROBE) recommendations consist of a checklist of 22
items that provide guidance on the reporting of cohort, case-control and
cross-sectional studies, in order to facilitate critical appraisal and
interpretation of results. STROBE was published in October 2007 in several
journals including The Lancet, BMJ, Annals of Internal Medicine and PLoS
Medicine. Within the framework of the revision of the STROBE recommendations, the
authors examined the context and circumstances in which the STROBE statement was
used in the past. Design The authors searched the Web of Science database in
August 2010 for articles which cited STROBE and examined a random sample of 100
articles using a standardised, piloted data extraction form. The use of STROBE in
observational studies and systematic reviews (including meta-analyses) was
classified as appropriate or inappropriate. The use of STROBE to guide the
reporting of observational studies was considered appropriate. Inappropriate uses
included the use of STROBE as a tool to assess the methodological quality of
studies or as a guideline on how to design and conduct studies. Results The
authors identified 640 articles that cited STROBE. In the random sample of 100
articles, about half were observational studies (32%) or systematic reviews
(19%). Comments, editorials and letters accounted for 15%, methodological
articles for 8%, and recommendations and narrative reviews for 26% of articles.
Of the 32 observational studies, 26 (81%) made appropriate use of STROBE, and
three uses (10%) were considered inappropriate. Among 19 systematic reviews, 10
(53%) used STROBE inappropriately as a tool to assess study quality. Conclusions
The STROBE reporting recommendations are frequently used inappropriately in
systematic reviews and meta-analyses as an instrument to assess the
methodological quality of observational studies
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