Accuracy of Promis-57 Depression and Anxiety Scales Compared to Legacy Instruments Among Kidney Transplant Recipients
Bibliographic record
Abstract
Background Depression and anxiety are frequent among kidney transplant recipients (KTRs). Patient reported outcome measures are used to assess these constructs, but concerns remain about measurement precision and questionnaire burden. The NIH PROsetta Stone project developed a common metric system which associates scores from scales measuring similar concepts across known legacy tools with the Patient Reported Outcomes Measurement System (PROMIS-57). Here, we evaluate the accuracy of the depression and anxiety domains of the PROMIS-57 profile questionnaire among KTRs. Methods Participants of this cross-sectional, convenience sample of stable KTRs completed the PROMIS-57 (includes PROMIS-29), Generalized Anxiety Disorder Scale (GAD-7) and Patient Health Questionnaire (PHQ-9) questionnaires. Raw scores of legacy tools (GAD-7 and PHQ-9) were converted to PROMIS T-scores using PROsetta Stone© crosswalk files. Spearman correlations were conducted between calculated PROMIS (from legacy scores), and reported PROMIS-57 scores. The cut off score of 10 on GAD-7 and PHQ-9 legacy scales were used to indicate clinically significant (moderate to severe) depression or anxiety, respectively. The corresponding PROsetta stone cut off scores on the reported PROMIS-57 and -29 scales were used to categorize severe to moderate depression and anxiety. We computed the sensitivity, specificity, positive predictive and negative predictive values for the categorization. Lastly, we calculated Cohens Kappa values to assess the degree of agreement between legacy instruments and respective PROMIS-57 and-29 domains to assign patients to “depression” and “anxiety” categories. Results Our sample included 150 KTRs (mean (±SD) age was 50 (±17) years, 57% male, 57% white. Based on legacy instruments, 7% had moderate to severe anxiety and 8% had depression while reported PROMIS-57 scores yielded 9% with anxiety and 11% with depression. Calculated anxiety scores showed strong correlations with reported PROMIS-57 (r=0.677, p<0.001), and PROMIS-29 (r=0.760, p<0.001) anxiety scores. Calculated depression scores showed strong correlations with reported PROMIS-57 (r=0.760, p<0.001), and PROMIS-29 (r=0.68, p<0.001) depression scores. The legacy cut offs used for severe to moderate anxiety and depression had high specificity (anxiety=0.95, depression=0.93) and moderate sensitivity (anxiety=0.70, depression=0.58). The Kappa values indicated moderate agreement between GAD-7 categorization of anxiety versus PROMIS-57 (K=0.55) and PROMIS-29 (K=0.56). Similarly, there was moderate agreement between PHQ-9 classification of depression versus PROMIS-57 (K=0.45) and PROMIS-29 (K=0.52). Conclusions The PROMIS-57 and -29 depression and anxiety domains are valid self-report tools that can be used to assess depressive and anxiety symptoms. Furthermore, the shorter questionnaire seems to be a good alternative to reduce questionnaire burden.
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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 | 0.022 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".