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Objectives Genome-wide association studies (GWAS) have identified loci associated with estimated glomerular filtration rate (eGFR). Few LN risk loci have been identified to date. We tested the association of SLE and eGFR polygenic risk scores (PRS) with repeated eGFR measures from children and adults with SLE. Methods Patients from two tertiary care lupus clinics that met ≥4 ACR and/or SLICC criteria for SLE were genotyped on the Illumina MEGA or Omni1-Quad arrays. PRSs were calculated for SLE and eGFR, using published weighted GWA-significant alleles. eGFR was calculated using the CKD-EPI and Schwartz equations. We tested the effect of eGFR- and SLE-PRSs on eGFR mean and variance, adjusting for age at diagnosis, sex, ancestry, follow-up time, and clinical event flags. Results We included 1158 SLE patients (37% biopsy-confirmed LN) with 36 733 eGFR measures over a median of 7.6 years (IQR: 3.9–15.3). LN was associated with lower within-person mean eGFR [LN: 93.8 (s. d. 26.4) vs non-LN: 101.6 (s. d. 17.7) mL/min per 1.73 m2 ; P  < 0.0001] and higher variance [LN median: 157.0 (IQR: 89.5, 268.9) vs non-LN median: 84.9 (IQR: 46.9, 138.2) (mL/min per 1.73 m2)2; P  < 0.0001]. Increasing SLE-PRSs were associated with lower mean eGFR and greater variance, while increasing eGFR-PRS was associated with increased eGFR mean and variance. Conclusion We observed significant associations between SLE and eGFR PRSs and repeated eGFR measurements, in a large cohort of children and adults with SLE. Longitudinal eGFR may serve as a powerful alternative outcome to LN categories for discovery of LN risk loci. [ABSTRACT FROM AUTHOR]

In comparing quality of care between hospitals, disease-specific quality indicators measure structural, process, or outcome elements related to the care of a particular condition. Such comparisons can be framed in terms of causal contrasts, answering the question of whether a patient (or a population of patients on average) would receive different care if treated at the care level of a different hospital. Fair comparisons have to be adjusted for patient case-mix, which is equivalent to controlling for confounding by the patient-level factors, including demographic factors, comorbidities, and disease progression. The methodological choice for such comparisons is usually between direct and indirect standardization methods. In this article, we discuss the alternative of inverse probability weighting as a tool for standardization in hospital comparisons. This involves fitting multinomial logistic hospital assignment models and using these to construct the inverse probability weights. The challenge in the present context is the presence of large number of hospitals being compared, many of which have a small patient volume. We propose methods to include small categories in the weighted analysis, as well as metrics and visualizations for checking the positivity/overlap and covariate balance in constructing such weights. The methods are illustrated in a running example using linked administrative data on surgical treatment of kidney cancer patients in Ontario. [ABSTRACT FROM AUTHOR]

The goal of radiation therapy for cancer is to deliver prescribed radiation dose to the tumor while minimizing dose to the surrounding healthy tissues. To evaluate treatment plans, the dose distribution to healthy organs is commonly summarized as dose-volume histograms (DVHs). Normal tissue complication probability (NTCP) modeling has centered around making patient-level risk predictions with features extracted from the DVHs, but few have considered adapting a causal framework to evaluate the safety of alternative treatment plans. We propose causal estimands for NTCP based on deterministic and stochastic interventions, as well as propose estimators based on marginal structural models that impose bivariable monotonicity between dose, volume, and toxicity risk. The properties of these estimators are studied through simulations, and their use is illustrated in the context of radiotherapy treatment of anal canal cancer patients., (© The Author(s) 2024. Published by Oxford University Press.)

Theatre testing (TT) method demonstrates whole or portions of an evidence-based intervention to stakeholders to elicit feedback on context-specific adaptations and future implementation. The Peer Navigator Project (PNP) studied the adaptation and implementation of Peer Navigators in five urban sites to increase street-connected youth (SCY) access to HIV prevention, testing, and treatment in Canada and Kenya. TT was used with SCY, healthcare providers, and community stakeholders to collect feedback on the optimal characteristics of the PNs (e.g., social identities) and their professional activities and responsibilities in each site. Sites scripted unique scenarios of PNs supporting SCY and interacting with social service providers. Local actors were employed, and the scenarios were filmed and edited into videos alongside audience discussion questions. Videos were screened to separate audiences of SCY ( n = 40), healthcare providers ( n = 12), and community stakeholders ( n = 59). Facilitated discussion about the scenarios were recorded as data, and transcripts were analyzed thematically by the research team. The scenario videos are presented as a unique adaptation to the TT method. The adaptations were time-consuming and limited the ability to present responsive changes while presenting the method to different audiences. They were also effective at maintaining presentation fidelity and eliciting diverse and meaningful responses from different stakeholder groups. One site successfully adapted the method for use in a physically distanced manner that complied with COVID-19 public health regulations. TT using video scenarios is an engaging approach that garners rich responses from diverse stakeholder groups about the adaptation of evidence-based interventions preparing for implementation in international settings., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 MacEntee, Lee, Oudshoorn, Abramovich, Kiptui, Ayuku, Van Berkum, Saarela, Tang, Apondi, Wachira, MacDonald and Braitstein.)