暂无摘要。

Observational data provide invaluable real-world information in medicine, but certain methodological considerations are required to derive causal estimates. In this systematic review, we evaluated the methodology and reporting quality of individual-level patient data meta-analyses (IPD-MAs) conducted with non-randomized exposures, published in 2009, 2014, and 2019 that sought to estimate a causal relationship in medicine. We screened over 16,000 titles and abstracts, reviewed 45 full-text articles out of the 167 deemed potentially eligible, and included 29 into the analysis. Unfortunately, we found that causal methodologies were rarely implemented, and reporting was generally poor across studies. Specifically, only three of the 29 articles used quasi-experimental methods, and no study used G-methods to adjust for time-varying confounding. To address these issues, we propose stronger collaborations between physicians and methodologists to ensure that causal methodologies are properly implemented in IPD-MAs. In addition, we put forward a suggested checklist of reporting guidelines for IPD-MAs that utilize causal methods. This checklist could improve reporting thereby potentially enhancing the quality and trustworthiness of IPD-MAs, which can be considered one of the most valuable sources of evidence for health policy.

BACKGROUND: Major depressive disorder (MDD) is highly prevalent and burdensome for individuals and society. While there are psychological interventions able to prevent and treat MDD, uptake remains low. To overcome structural and attitudinal barriers, an indirect approach of using online insomnia interventions seems promising because insomnia is less stigmatized, predicts MDD onset, is often comorbid and can outlast MDD treatment. This individual-participant-data meta-analysis evaluated the potential of the online insomnia intervention GET.ON Recovery as an indirect treatment to reduce depressive symptom severity (DSS) and potential MDD onset across a range of participant characteristics.
METHODS: Efficacy on depressive symptom outcomes was evaluated using multilevel regression models controlling for baseline severity. To identify potential effect moderators, clinical, sociodemographic, and work-related variables were investigated using univariable moderation and random-forest methodology before developing a multivariable decision tree.
RESULTS: IPD were obtained from four of seven eligible studies (N = 561); concentrating on workers with high work-stress. DSS was significantly lower in the intervention group both at post-assessment (d = -0.71 [95% CI-0.92 to -0.51]) and at follow-up (d = -0.84 [95% CI -1.11 to -0.57]). In the subsample (n = 121) without potential MDD at baseline, there were no significant group differences in onset of potential MDD. Moderation analyses revealed that effects on DSS differed significantly across baseline severity groups with effect sizes between d = -0.48 and -0.87 (post) and d = - 0.66 to -0.99 (follow-up), while no other sociodemographic, clinical, or work-related characteristics were significant moderators.
CONCLUSIONS: An online insomnia intervention is a promising approach to effectively reduce DSS in a preventive and treatment setting.

BACKGROUND: The provision of data sharing statements (DSS) for clinical trials has been made mandatory by different stakeholders. DSS are a device to clarify whether there is intention to share individual participant data (IPD). What is missing is a detailed assessment of whether DSS are providing clear and understandable information about the conditions for data sharing of IPD for secondary use.
METHODS: A random sample of 200 COVID-19 clinical trials with explicit DSS was drawn from the ECRIN clinical research metadata repository. The DSS were assessed and classified, by two experienced experts and one assessor with less experience in data sharing (DS), into different categories (unclear, no sharing, no plans, yes but vague, yes on request, yes with specified storage location, yes but with complex conditions).
RESULTS: Between the two experts the agreement was moderate to substantial (kappa=0.62, 95% CI [0.55, 0.70]). Agreement considerably decreased when these experts were compared with a third person who was less experienced and trained in data sharing (\"assessor\") (kappa=0.33, 95% CI [0.25, 0.41]; 0.35, 95% CI [0.27, 0.43]). Between the two experts and under supervision of an independent moderator, a consensus was achieved for those cases, where both experts had disagreed, and the result was used as \"gold standard\" for further analysis. At least some degree of willingness of DS (data sharing) was expressed in 63.5% (127/200) cases. Of these cases, around one quarter (31/127) were vague statements of support for data sharing but without useful detail. In around half of the cases (60/127) it was stated that IPD could be obtained by request. Only in in slightly more than 10% of the cases (15/127) it was stated that the IPD would be transferred to a specific data repository. In the remaining cases (21/127), a more complex regime was described or referenced, which could not be allocated to one of the three previous groups. As a result of the consensus meetings, the classification system was updated.
CONCLUSIONS: The study showed that the current DSS that imply possible data sharing are often not easy to interpret, even by relatively experienced staff. Machine based interpretation, which would be necessary for any practical application, is currently not possible. Machine learning and / or natural language processing techniques might improve machine actionability, but would represent a very substantial investment of research effort. The cheaper and easier option would be for data providers, data requestors, funders and platforms to adopt a clearer, more structured and more standardised approach to specifying, providing and collecting DSS.
BACKGROUND: The protocol for the study was pre-registered on ZENODO ( https://zenodo.org/record/7064624#.Y4DIAHbMJD8 ).

BACKGROUND: Induction of labour (IOL) is common practice and different methods carry different effectiveness and safety profiles.
OBJECTIVE: To compare the effectiveness, and maternal and perinatal safety outcomes of IOL with vaginal misoprostol versus vaginal dinoprostone using individual participant data from randomised clinical trials.
METHODS: The following databases were searched from inception to March 2023: CINAHL Plus, ClinicalTrials.gov, Cochrane Pregnancy and Childbirth Group Trial Register, Ovid Embase, Ovid Emcare, Ovid MEDLINE, Scopus and the World Health Organization (WHO) International Clinical Trials Registry Platform (ICTRP).
METHODS: Randomised controlled trials (RCTs), with viable singleton gestation, no language restrictions, and all published and unpublished data.
METHODS: An individual participant data meta-analysis was carried out.
RESULTS: Ten of 52 eligible trials provided individual participant data, of which two were excluded after checking data integrity. The remaining eight trials compared low-dose vaginal misoprostol versus dinoprostone, including 4180 women undergoing IOL, which represents 32.8% of all participants in the published RCTs. Of these, 2077 were assigned to low-dose vaginal misoprostol and 2103 were assigned to vaginal dinoprostone. Compared with vaginal dinoprostone, low-dose vaginal misoprostol had a comparable rate of vaginal birth. Composite adverse perinatal outcomes did not differ between the groups. Compared with vaginal dinoprostone, composite adverse maternal outcomes were significantly lower with low-dose vaginal misoprostol (aOR 0.80, 95% CI 0.65-0.98, P = 0.03, I2 = 0%).
CONCLUSIONS: Low-dose vaginal misoprostol and vaginal dinoprostone for IOL are comparable in terms of effectiveness and perinatal safety. However, low-dose vaginal misoprostol is likely to lead to a lower rate of composite adverse maternal outcomes than vaginal dinoprostone.

There is insufficient investigation of multiple imputation for systematically missing discrete variables in individual participant data meta-analysis (IPDMA) with a small number of included studies. Therefore, this study aims to evaluate the performance of three multiple imputation strategies - fully conditional specification (FCS), multivariate normal (MVN), conditional quantile imputation (CQI) - on systematically missing data on gait speed in the Swedish National Study on Aging and Care (SNAC).
In total, 1 000 IPDMA were simulated with four prospective cohort studies based on the characteristics of the SNAC. The three multiple imputation strategies were analysed with a two-stage common-effect multivariable logistic model targeting the effect of three levels of gait speed (100% missing in one study) on 5-years mortality with common odds ratios set to OR1 = 0.55 (0.8-1.2 vs ≤0.8 m/s), and OR2 = 0.29 (>1.2 vs ≤0.8 m/s).
The average combined estimate for the mortality odds ratio OR1 (relative bias %) were 0.58 (8.2%), 0.58 (7.5%), and 0.55 (0.7%) for the FCS, MVN, and CQI, respectively. The average combined estimate for the mortality odds ratio OR2 (relative bias %) were 0.30 (2.5%), 0.33 (10.0%), and 0.29 (0.9%) for the FCS, MVN, and CQI respectively.
In our simulations of an IPDMA based on the SNAC where gait speed data was systematically missing in one study, all three imputation methods performed relatively well. The smallest bias was found for the CQI approach.

BACKGROUND: Selective reporting of results from only well-performing cut-offs leads to biased estimates of accuracy in primary studies of questionnaire-based screening tools and in meta-analyses that synthesize results. Individual participant data meta-analysis (IPDMA) of sensitivity and specificity at each cut-off via bivariate random-effects models (BREMs) can overcome this problem. However, IPDMA is laborious and depends on the ability to successfully obtain primary datasets, and BREMs ignore the correlation between cut-offs within primary studies.
METHODS: We compared the performance of three recent multiple cut-off models developed by Steinhauser et al., Jones et al., and Hoyer and Kuss, that account for missing cut-offs when meta-analyzing diagnostic accuracy studies with multiple cut-offs, to BREMs fitted at each cut-off. We used data from 22 studies of the accuracy of the Edinburgh Postnatal Depression Scale (EPDS; 4475 participants, 758 major depression cases). We fitted each of the three multiple cut-off models and BREMs to a dataset with results from only published cut-offs from each study (published data) and an IPD dataset with results for all cut-offs (full IPD data). We estimated pooled sensitivity and specificity with 95% confidence intervals (CIs) for each cut-off and the area under the curve.
RESULTS: Compared to the BREMs fitted to the full IPD data, the Steinhauser et al., Jones et al., and Hoyer and Kuss models fitted to the published data produced similar receiver operating characteristic curves; though, the Hoyer and Kuss model had lower area under the curve, mainly due to estimating slightly lower sensitivity at lower cut-offs. When fitting the three multiple cut-off models to the full IPD data, a similar pattern of results was observed. Importantly, all models had similar 95% CIs for sensitivity and specificity, and the CI width increased with cut-off levels for sensitivity and decreased with an increasing cut-off for specificity, even the BREMs which treat each cut-off separately.
CONCLUSIONS: Multiple cut-off models appear to be the favorable methods when only published data are available. While collecting IPD is expensive and time consuming, IPD can facilitate subgroup analyses that cannot be conducted with published data only.

UNASSIGNED: Numerous arguments have been advanced for broadly sharing de-identified, participant-level clinical trial data. However, data sharing in pragmatic clinical trials (PCTs) presents ethical challenges. While prior scholarship has described aspects of PCTs that raise distinct considerations for data sharing, there have been no reports of the experiences of those at the leading edge of data-sharing efforts for PCTs, including how these particular challenges have been navigated. To address this gap, we conducted interviews with key stakeholders, with a focus on the ethical issues presented by sharing data from PCTs.
UNASSIGNED: We recruited respondents using purposive sampling to reflect the range of stakeholder groups affected by efforts to expand PCT data sharing. Through semi-structured interviews, we explored respondents\' experiences and perceptions about sharing de-identified, individual-level data from PCTs. An integrated approach was used to identify and describe key themes.
UNASSIGNED: We conducted 40 interviews between April and September 2022. Five overarching themes emerged through analysis: (1) challenges in sharing data collected under a waiver or alteration of consent; (2) conflicting views regarding PCT patient-subject preferences for data sharing; (3) identification of respect-promoting practices beyond consent; (4) concerns about elevated risks or burdens from sharing PCT data; and (5) diverse views about the likely benefits resulting from sharing PCT data.
UNASSIGNED: Our data indicate unresolved tensions in how to fulfill the expectation to broadly share de-identified, individual-level data from PCTs, and suggest that those promulgating and implementing data-sharing policies must be sensitive to PCT-specific considerations. Future work could inform efforts to tailor data-sharing policy and practice to reflect the challenges presented by PCTs, including sharing experiences from trials that have successfully navigated these tensions.

BACKGROUND: IVF and IUI with ovarian stimulation (IUI-OS) are widely used in managing unexplained infertility. IUI-OS is generally considered first-line therapy, followed by IVF only if IUI-OS is unsuccessful after several attempts. However, there is a growing interest in using IVF for immediate treatment because it is believed to lead to higher live birth rates and shorter time to pregnancy.
OBJECTIVE: Randomized controlled trials (RCTs) comparing IVF versus IUI-OS had varied study designs and findings. Some RCTs used complex algorithms to combine IVF and IUI-OS, while others had unequal follow-up time between arms or compared treatments on a per-cycle basis, which introduced biases. Comparing cumulative live birth rates of IVF and IUI-OS within a consistent time frame is necessary for a fair head-to-head comparison. Previous meta-analyses of RCTs did not consider the time it takes to achieve pregnancy, which is not possible using aggregate data. Individual participant data meta-analysis (IPD-MA) allows standardization of follow-up time in different trials and time-to-event analysis methods. We performed this IPD-MA to investigate if IVF increases cumulative live birth rate considering the time leading to pregnancy and reduces multiple pregnancy rate compared to IUI-OS in couples with unexplained infertility.
METHODS: We searched MEDLINE, EMBASE, CENTRAL, PsycINFO, CINAHL, and the Cochrane Gynaecology and Fertility Group Specialised Register to identify RCTs that completed data collection before June 2021. A search update was carried out in January 2023. RCTs that compared IVF/ICSI to IUI-OS in couples with unexplained infertility were eligible. We invited author groups of eligible studies to join the IPD-MA and share the deidentified IPD of their RCTs. IPD were checked and standardized before synthesis. The quality of evidence was assessed using the Risk of Bias 2 tool.
RESULTS: Of eight potentially eligible RCTs, two were considered awaiting classification. In the other six trials, four shared IPD of 934 women, of which 550 were allocated to IVF and 383 to IUI-OS. Because the interventions were unable to blind, two RCTs had a high risk of bias, one had some concerns, and one had a low risk of bias. Considering the time to pregnancy leading to live birth, the cumulative live birth rate was not significantly higher in IVF compared to that in IUI-OS (4 RCTs, 908 women, 50.3% versus 43.2%, hazard ratio 1.19, 95% CI 0.81-1.74, I2 = 42.4%). For the safety primary outcome, the rate of multiple pregnancy was not significantly lower in IVF than IUI-OS (3 RCTs, 890 women, 3.8% versus 5.2% of all couples randomized, odds ratio 0.78, 95% CI 0.41-1.50, I2 = 0.0%).
CONCLUSIONS: There is no robust evidence that in couples with unexplained infertility IVF achieves pregnancy leading to live birth faster than IUI-OS. IVF and IUI-OS are both viable options in terms of effectiveness and safety for managing unexplained infertility. The associated costs of interventions and the preference of couples need to be weighed in clinical decision-making.

Visceral leishmaniasis (VL) is a parasitic disease with an estimated 30 000 new cases occurring annually. Despite anaemia being a common haematological manifestation of VL, the evolution of different haematological characteristics following treatment remains poorly understood. An individual participant data meta-analysis (IPD-MA) is planned to characterise the haematological dynamics in patients with VL.
The Infectious Diseases Data Observatory (IDDO) VL data platform is a global repository of IPD from therapeutic studies identified through a systematic search of published literature (PROSPERO registration: CRD42021284622). The platform currently holds datasets from clinical trials standardised to a common data format. Corresponding authors and principal investigators of the studies indexed in the IDDO VL data platform meeting the eligibility criteria for inclusion were invited to be part of the collaborative IPD-MA. Mixed-effects multivariable regression models will be constructed to identify determinants of haematological parameters by taking clustering within study sites into account.
This IPD-MA meets the criteria for waiver of ethical review as defined by the Oxford Tropical Research Ethics Committee (OxTREC) granted to IDDO, as the research consists of secondary analysis of existing anonymised data (exempt granted on 29 March 2023, OxTREC REF: IDDO). Ethics approval was granted by the ICMR-Rajendra Memorial Research Institute of Medical Sciences ethics committee (letter no.: RMRI/EC/30/2022) on 4 July 2022. The results of this analysis will be disseminated at conferences, the IDDO website and peer-reviewed publications in open-access journals. The findings of this research will be critically important for control programmes at regional and global levels, policymakers and groups developing new VL treatments.
CRD42021284622.