Association of Drug Effects on Serum Parathyroid Hormone, Phosphorus, and Calcium Levels With Mortality in CKD: A Meta-analysis
Bibliographic record
Abstract
BACKGROUND: Serum parathyroid hormone (PTH), phosphorus, and calcium levels are surrogate outcomes that are central to the evaluation of drug treatments in chronic kidney disease (CKD). This systematic review evaluates the evidence for the correlation between drug effects on biochemical (PTH, phosphorus, and calcium) and all-cause and cardiovascular mortality end points in adults with CKD. STUDY DESIGN: Systematic review and meta-analysis. SETTING & POPULATION: Adults with CKD. SELECTION CRITERIA FOR STUDIES: Randomized trials reporting drug effects on biochemical and mortality end points. INTERVENTION: Drug interventions with effects on serum PTH, phosphorus, and calcium levels, including vitamin D compounds, phosphate binders, cinacalcet, bisphosphonates, and calcitonin. OUTCOMES: Correlation between drug effects on biochemical and all-cause and cardiovascular mortality. RESULTS: 28 studies (6,999 participants) reported both biochemical and mortality outcomes and were eligible for analysis. Associations between drug effects on surrogate biochemical end points and corresponding effects on mortality were weak and imprecise. All correlation coefficients were less than 0.70, and 95% credible intervals were generally wide and overlapped with zero, consistent with the possibility of no association. The exception was an inverse correlation between drug effects on serum PTH levels and all-cause mortality, which was nominally significant (-0.64; 95% credible interval, -0.85 to -0.15), but the strength of this association was very imprecise. Risk of bias within available trials was generally high, further reducing confidence in the summary correlations. Findings were robust to adjustment for age, baseline serum PTH level, allocation concealment, CKD stage, and drug class. LIMITATIONS: Low power in analyses and combining evidence from many different drug comparisons with incomplete data across studies. CONCLUSIONS: Drug effects on serum PTH, phosphorus, and calcium levels are weakly and imprecisely correlated with all-cause and cardiovascular death in the setting of CKD. Risks of mortality (patient-level outcome) cannot be inferred from treatment-induced changes in biochemical outcomes in people with CKD. Similarly, existing data do not exclude a mortality benefit with treatment. Trials need to address patient-centered outcomes to evaluate drug effectiveness in this setting.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.026 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".