Oral magnesium supplements for cancer treatment‐induced hypomagnesemia: Results from a pilot randomized trial
Bibliographic record
Abstract
Abstract Background and Aims Optimal management of cancer treatment‐induced hypomagnesemia (hMg) is not known. We assessed the feasibility of using a novel pragmatic clinical trials model to compare two commonly used oral Mg replacement strategies. Methods Patients with grade 1 to 3 hMg while receiving either platinum‐based chemotherapy or epidermal growth factor receptor inhibitors (EGFRI) were randomized to oral magnesium oxide (MgOx) or oral magnesium citrate (MgCit). The trial methodology utilized the integrated consent model. Feasibility would be successful if; accrual rate was ≥5 patients a month and if measures of patient and physician engagement, were > 50%. Secondary endpoints included; comparison of Mg levels, cardiac arrhythmias, and rates of treatment delay/hospitalizations. Results From July 2016 to December 2017, an average of 1 patient a month was accrued. All 15 eligible and approached patients consented to participate in the study (100% engagement) and 7/15 were randomized to MgOx and 8/15 to MgCit. The percentage of physicians who approached patients for the study was 4 of 6 (66.6% engagement). The mean slope of change in Mg (mmol/L/day) was 0.0022 (95% CI: −0.0001 to 0.0044) for MgOx and 0.0006 (95% CI, −0.0012 to 0.0024) for MgCit (P = .2123). Three patients (20%) required IV magnesium while on the study (2 MgCit and 1 MgOx). Grade 1 diarrhea occurred in 3 patients in the MgCit arm. Conclusion Despite oral magnesium tolerability and meeting most of its feasibility endpoints, this study did not meet its target accrual rate. Alternative designs would be necessary for a definitive efficacy study.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".