THE OUTCOMES AND VALUE OF EARLY DIAGNOSIS IN ACHIEVING REMISSION FOR SYSTEMIC LUPUS ERYTHEMATOSUS PATIENTS (OVERSLEEP STUDY): AN INTERIM REPORT.
Bibliographic record
Abstract
PV227 / #356 Poster Topic: AS23 - SLE-Diagnosis, Manifestations, & Outcomes Background/Purpose The definition of “early systemic lupus erythematosus (SLE)” is evolving as we recognize the importance of identifying symptoms and initiating treatment earlier to prevent organ damage and improve both short- and long-term outcomes.[1] Several definitions of early SLE have been proposed concerning the time elapsed since symptom onset, ranging from <6 months to <36 months, with no general agreement. The OVERSLEEP study was designed to investigate whether there is a critical window of opportunity to establish an early diagnosis to improve the chances of achieving remission in SLE and prevent further damage once treatment begins. Methods OVERSLEEP is a multicenter (23 centers), prospective, observational study ideated by the Italian Society of Rheumatology’s study group on early SLE. Eligible individuals are newly diagnosed SLE patients, fulfilling at least 1 of the validated sets of classification criteria. Diagnostic delay is defined as the time when symptoms are first presented to a healthcare provider (eg, general practitioner, lab, specialist, emergency room) until a diagnosis is made. Visits at 6-month intervals, or earlier if needed, assess clinical and laboratory features. The primary endpoint is the achievement of remission after 6 months. Secondary endpoints are LLDAS, organ damage according to the SLICC/ACR damage index, flares, patient-reported outcomes, hospitalizations, and death. Primary statistical analysis will be performed by logistic regression with the primary endpoint as the dependent variable, including diagnostic delay as the exposure variable and several adjustment variables. This abstract reports on the selection process for the adjustment variables associated with delayed diagnosis calculated as the “diagnostic delay ratio” between groups with or without the reference variable (ie, Mean delay-time interest group/Mean delay-time reference group). Results Enrollment started in September 2020 and aims at a sample size of 420 patients. In October 2024, the study included 221 patients (84.1% female); the median age is 38.0 (IQR 25.0 – 48.0) years, and 90% are Caucasians. The primary endpoint of remission at 6 months since diagnosis is achieved by 45 patients (25.6%). Univariate analysis identified factors associated with delayed diagnosis (Table 1), which, if confirmed in the whole study sample, will be used as adjustment variables, including baseline treatment with the daily and cumulative dose of glucocorticoids. The directed acyclic graph in Figure 1 shows the potential causal relationship between variables, identifying variables that will be included in the final model for primary statistical analysis of the OVERSLEEP study. The ancestor of exposure and outcome are confounders and will be included in the final model as adjustment factors. Table 1. Baseline variables and diagnostic delay ratio between the reference group and the interest group. F variable sex, the reference class is “female,” and the interest class is male; the diagnostic delay ratio is 1.46, means that males have a 46% mean time delay in diagnosis compared to females. Figure 1. Conclusions The OVERSLEEP study targets a population in which remission is observable within 6 months of diagnosis. The enrolled population showed factors associated with delayed diagnosis, which are of interest for modeling the analysis of the OVERSLEEP study and further investigation aiming at developing red flags for early SLE diagnosis. *Listed authors have enrolled at least 10 patients with completed primary endpoint. References: [1.] Piga M. Best Pract Res Clin Rheumatol 2023;37(4):101938.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".