The toxicity gap: Do real-life patients get hospitalized more during chemotherapy compared to trial patients?
Bibliographic record
Abstract
109 Background: Toxicity related hospitalizations during chemotherapy are poorly reported in the literature. We sought to compare “real world” versus clinical trial rates of hospitalizations among patients with metastatic non-small cell lung cancer (mNSCLC) receiving chemotherapy. We hypothesised that hospitalization rates in real life patients would be significantly higher. Methods: We conducted a systematic review of Medline and EMBASE (1946-June 2013) to identify articles reporting hospitalization rates during chemotherapy in patients with cancer. Both observational studies and clinical trials were eligible. This report focuses on patients with mNSCLC receiving palliative chemotherapy as data was available for this clinical scenario in both the observational and clinical trial setting, allowing comparison. Study results were abstracted using a standardised form. Summary statistics were used to describe results and the chi-square test used to compare hospitalization rates. Results: The search identified 61 articles (all published after 1987), of which 16 were clinical trials and 45 were observational (“real world”) studies. Nine studies examined chemotherapy in mNSCLC - four observational studies and five randomised trials. The four observational studies included 7,456 patients; three included patients on any chemotherapy while the other focused on doublet regimens. Of the five randomised trials which included 3,962 patients, three treated patients with platinum doublets and two used single-agent chemotherapy. The real life cohort was older (70 years vs. 62 years). The aggregate hospitalization rate among real life patients was significantly higher than among trial patients (49% vs. 16%, OR=7.7, 95% CI 7-8.5, p-value < 0.0001). Performance status and type of chemotherapy were associated with hospitalization during chemotherapy in clinical trials while type of chemotherapy was a risk factor in observational studies. Conclusions: Clinical trials in mNSCLC consistently report lower rates of hospitalization than real life cohorts of patients undergoing similar therapies but very few clinical trials report this information.
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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 | 0.036 | 0.189 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".