Measuring chemotherapy safety in a community oncology practice: Results of a three-year prospective study
Bibliographic record
Abstract
6019 Background: Chemotherapy administration is associated with a risk for severe toxicity and mortality. Limited data are available to assess these risks outside of clinical trials or administrative databases. We sought to determine the risk of chemotherapy administration in a community-based oncology practice, to identify potential risk factors, and to look for trends over time. Methods: The North Shore Medical Center Cancer Center (NSCC) is a community-based cancer facility in Peabody, MA. In 1/03, we began a prospective study to identify and categorize all adult patients admitted to hospital with severe chemotherapy toxicity and to compare them to all chemotherapy recipients. Consecutive cases admitted to hospital from NSCC were reviewed in a monthly multidisciplinary peer review meeting. Admissions deemed to be treatment-related were entered into a toxicity database. Results: Between 1/1/03 and 11/30/05, 2206 courses of chemotherapy were administered to 1574 patients resulting in 12,380 treatment-months of therapy. 162 patients required 174 hospital admissions, for an annualized risk of treatment-related hospitalization (TRH) of 16.6% and a mean length of stay of 7.0 days. Mean age of cases was similar for those admitted for toxicity compared to all chemotherapy patients (65.3 versus 64.6 yrs.). GI toxicity and infection (principally fever and neutropenia) accounted for 77% of TRH. Between 2003 and 2005, the risk of a TRH declined for colorectal cancer cases while it increased for breast cancer and lung cancer cases. There were 14 treatment-related deaths (TRD) for an annualized risk of 1.1%. TRD’s were infectious in 9, GI in 4 and cardiac in 1. Median age was 67, similar to the entire cohort. TRD occurred early (median 28 days from the inception of chemotherapy, range 1–120 days). Significant comorbidity was identifiable in 12 of 14 cases. 10 of 14 cases were being treated palliatively. Conclusions: These prospectively collected data confirm that chemotherapy administration in a community-based practice can be associated with a low risk of severe toxicity and a very low risk of mortality. TRH and TRD could become standard measures of quality care for cancer facilities. No significant financial relationships to disclose.
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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 | 0.019 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".