Effectiveness and safety of pneumocystis pneumonia prophylaxis for patients receiving temozolomide chemoradiotherapy
Bibliographic record
Abstract
BACKGROUND: Malignant gliomas are treated with temozolomide chemoradiotherapy. Because pneumocystis pneumonia (PCP) can occur in patients receiving temozolomide, the product monograph recommends PCP prophylaxis during temozolomide chemoradiotherapy. Not all neuro-oncologists follow these recommendations, though. METHODS: We performed a population-based retrospective cohort study of glioma patients undergoing temozolomide chemoradiotherapy 2005 to 2019 in Ontario, Canada. A propensity score model was used to predict the use of PCP prophylaxis. We compared the risk of PCP within 90 days of starting radiotherapy with versus without PCP prophylaxis using inverse probability of treatment weighting (IPTW). We also examined overall survival, hospitalizations, and myelosuppression. RESULTS: There were 3,225 patients included in the cohort (648 received antibiotics and 2,434 did not). Only 18 patients developed PCP within 90 days of therapy. The IPTW-adjusted absolute risk reduction in PCP with antibiotics was 0.0035 (95% CI, -0.0013 to 0.0083), number needed to treat: 288. Neither overall survival nor hospitalization count differed between the groups. The number needed to harm by causing grade 3/4 neutropenia was 39. CONCLUSIONS: In regions (like Ontario) where PCP is rare, routine PCP prophylaxis with trimethoprim-sulfamethoxazole should not be offered, since the harms may outweigh the benefits.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".