Original Contribution Hepatitis B Screening Before Chemotherapy: A Survey of Practitioners ’ Knowledge, Beliefs, and Screening Practices
Bibliographic record
Abstract
Purpose: Hepatitis B virus (HBV) reactivation is a potentially fatal complication of chemotherapy that can be largely prevented with medication, provided that asymptomatic HBV carriers are identified. We explored the knowledge, beliefs, and practices of Canadian oncologists/hematologists regarding HBV screening before chemotherapy. Methods: A novel questionnaire was mailed to all practicing hematologists/oncologists, where publicly accessible online physician registries facilitated identification of these specialists (71 % of the Canadian physician population). Results: Of 504 potentially eligible practitioners, 311 (62%) responded, of whom 246 indicated that they administered che-motherapy and were thus included in final analyses. Respon-dents tended to underestimate the risk of HBV reactivation, and recognition of the major risk factor for HBV carriage (ie, birth in an endemic area) was low. Forty percent of respondents reported rarely or never testing for HBV before chemotherapy, and 36% reported screening only those patients with HBV risk factors. In multivariate analysis, having a predominantly hematologic prac-tice, practitioner experience with HBV reactivation, ability to cor-rectly estimate the risk of HBV reactivation, fewer years in practice, and female sex were independently associated with an increased likelihood of screening for HBV. Conclusion: Canadian oncologists and hematologists tend to underestimate the risk of HBV reactivation and report relatively low HBV screening rates. Among those practitioners who do screen, the favored strategy is selective screening of patients with HBV risk factors. However, oncologists’/hematologists’ knowledge regarding risk factors for HBV carriage seems to be low, potentially undermining the success of a selective screening strategy.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 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) | 0.004 | 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".