Observational studyBMJ open2023
Risk Indicators of Sarcoidosis Evolution-Unified Protocol (RISE-UP): protocol for a multi-centre, longitudinal, observational study to identify clinical features that are predictive of sarcoidosis progression.
Observational study in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05567133 (Development of Clinical Prediction Models for Pulmonary Outcomes in Sarcoidosis), which is not on this map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Development of Clinical Prediction Models for Pulmonary Outcomes in Sarcoidosis
Who cites it
1 citing paper in PubMed, 3 citations in OpenAlex.
- High-Risk Sarcoidosis: A Focus on Pulmonary, Cardiac, Hepatic and Renal Advanced Diseases, as Well as on Calcium Metabolism Abnormalities.Diagnostics (Basel, Switzerland) · 2024Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 4 institutions in 1 country.
Funding
Abstract
introductionSarcoidosis is a pulmonary and systemic granulomatous disease with a wide range of potential outcomes, from spontaneous resolution to end-stage organ damage and death. Currently, clinicians have no easy-to-use risk stratification tools for important clinical outcomes in sarcoidosis, such as progressive lung disease. This study will address two clinical practice needs: (1) development of a risk calculator that provides an estimate of the likelihood of pulmonary progression in sarcoidosis patients during the follow-up period and (2) determine the optimal interval for serial clinical monitoring (eg, 6, 12, 18 months) using these risk prediction tools. METHODS AND ANALYSIS: The Risk Indicators of Sarcoidosis Evolution-Unified Protocol study is a National Institutes of Health-sponsored, longitudinal observational study of adults with pulmonary sarcoidosis who will be enrolled at five US tertiary care centres. Participants will be evaluated at approximately 6-month intervals for up to 60 months with collection of lung function, blood samples and clinical data. The target sample size is 557 and the primary objective is to determine which clinical features measured during a routine clinic visit carry the most prognostic information for predicting clinical progression of pulmonary sarcoidosis over the follow-up period. The primary outcome measure will be quantified by a clinically meaningful change in forced vital capacity, forced expiratory volume in 1 s or diffusing capacity of the lung for carbon monoxide. The secondary objective is to determine if blood biomarkers measured during a routine clinic visit can improve the risk assessment modelling for progression of pulmonary sarcoidosis over the follow-up period. ETHICS AND DISSEMINATION: The study protocol has been approved by the Institutional Review Boards at each centre and the reliance Institutional Review Board overseeing the study (WCG, Protocol #20222400). Participants will provide informed consent prior to enrolment. Results will be disseminated via publication in a relevant peer-reviewed journal. TRIAL REGISTRATION NUMBER: NCT05567133.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.