PROMIS Provides a Broader Overview of Health-related Quality of Life Than the ESSPRI in Evaluation of Sjögren Syndrome
Bibliographic record
Abstract
Objective Sjögren syndrome (SS) has a significant impact on health-related quality of life (HRQOL). We sought to evaluate how the Patient Reported Outcome Measurement Information System (PROMIS) domains in SS may supplement the European League Against Rheumatism (EULAR) Sjögren Syndrome Patient Reported Index (ESSPRI). Methods A cross-sectional evaluation was performed on consecutive adult patients during visits to an SS clinic between March 2018 and February 2020. Each patient completed PROMIS short forms related to HRQOL and the ESSPRI, and had a clinical assessment. Patients were either classified as SS by 2016 American College of Rheumatology (ACR)/EULAR criteria, or as “sicca not otherwise specified (NOS)” and used as a comparison group. Univariable and multivariable linear regression models were used to evaluate predictors of PROMIS fatigue (-F), pain interference (-PI), and ability to participate in social roles and activities (-APS). Results Two hundred twenty-seven patients with SS and 85 with sicca NOS were included and did not differ in ESSPRI domains; 26% of the SS and 20% of the sicca NOS group had concurrent autoimmune disease. In SS, PROMIS-PI, PROMIS-F, and PROMIS physical function were at least one-half SD worse than US population normative values. PROMIS-PI ( r = 0.73) and PROMIS-F ( r = 0.80) were highly correlated with ESSPRI pain and fatigue subdomains. Fatigue and pain interference, but not dryness or mood disturbance, were the strongest predictors of social participation in multivariable analysis. Conclusion In our SS cohort, PROMIS instruments identified a high disease burden of pain interference, fatigue, and physical function. PROMIS-F strongly predicted PROMIS-APS. PROMIS-PI and PROMIS-F scores correlated highly with their respective ESSPRI domains. PROMIS instruments should be considered to identify relevant HRQOL patterns in SS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".