The Urine Protein-Albumin Gap as a Predictor of Multiple Myeloma
Bibliographic record
Abstract
Background: Multiple myeloma (MM) frequently presents as an unexplained decline in kidney function. Nephrologists often assess for discordance between the urine protein-creatinine ratio (UPCR) and urine albumin-creatinine ratio (UACR) as a proxy for free light chains in the urine consistent with cast nephropathy. However, thresholds for the urine protein-albumin gap (UPCR-UACR) and its association with MM are not well established. Methods: We conducted a population-level, retrospective cohort study of adults in Ontario, Canada with same day measurements of UPCR/UACR and without a history of MM between 2009-2021 (N=28,231) using provincial health data. Individuals were categorized by quartile of urine protein-albumin gap and stratified by UPCR (≤ or >50 mg/mmol). Multivariable Cox regression models estimated the association between the urine protein-albumin gap and MM. Results: 116 individuals were diagnosed with MM (0.4%) at a median time of 31 days. In the overall cohort, MM diagnoses increased with each successive quartile of urine protein-albumin gap (Fig. A). However, compared to Quartile 1 (≤9.3 mg/mmol), only Quartile 4 (>43.4 mg/mmol) was associated with a significantly higher risk for MM (HR 4.49 [95%CI 2.47-8.15]). Among individuals with a UPCR≤50 mg/mmol, no association was observed (Fig. B). In contrast, among individuals with a UPCR>50 mg/mmol, a higher urine protein-albumin gap was associated with a higher risk of MM (Q1 ≤34.2 mg/mmol: ref, Q2 34.3-57.5 mg/mmol: HR 1.98 [95%CI 0.59-6.62], Q3 57.6-111.8 mg/mmol: HR 3.94 [95%CI 1.29-11.97], and Q4 >111.8 mg/mmol: HR 10.97 [95%CI 3.85-31.25]; Fig. C). Conclusions: The urine protein-albumin gap is associated with MM, predominantly when the UPCR is >50 mg/mmol and the urine protein-albumin gap exceeds ˜50 mg/mmol. These results establish clinically meaningful thresholds for clinicians to utilize when interpreting discordance between UPCR and UACR values as a predictor of MM in cases of unexplained kidney dysfunction.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".