Positron-Emission Tomography for Locally Advanced Cervical Cancer: A Survey Assessing Canadian Practice Patterns and Access
Bibliographic record
Abstract
PURPOSE: Imaging by fluorodeoxyglucose positron-emission tomography (pet) has emerged as a valuable tool in the management of locally advanced cervical cancer (lacc), both for assessment of lymph node status and determination of response to chemoradiotherapy. The aim of the present study was to survey Canadian radiation oncologists to determine access to pet imaging for lacc patients and to assess current patterns of practice. METHODS: Radiation oncology centres across Canada were contacted to identify radiation oncologists who treat patients with lacc. The focus of the survey was patients treated with radical chemoradiotherapy with curative intent. An anonymous online tool was used to distribute a 23-item questionnaire asking about access to pet imaging, opinions on indications for pet imaging, and practice patterns relating to the use of pet in this patient population. Questionnaire responses were tabulated and analyzed. RESULTS: The response rate was 65% (35 of 54 questionnaire recipients). Most respondents (80%) have access to pet for lacc patients, usually restricted to study protocols. Of the respondents,48% considered that access to pet was timely. Frequency of routine orders for pet before and after treatment (to assess response) was 63% and 15% respectively. With better access, 91% of respondents would routinely order pet before treatment, and 61% would routinely order it for posttreatment assessment. For initial staging, 85% of respondents considered pet to be a standard of care, and nearly half (45%) believed it should be a standard of care to assess treatment response. Because of access limitations, nearly 70% of respondents (23 of 34) do not order pet as often as they feel it is clinically indicated, and 74% agree that better access to pet would lead to improved care for lacc patients in Canada. CONCLUSIONS: Canadian radiation oncologists support the routine use of pet imaging in the initial workup of patients with lacc. Access to pet imaging limits routine use for these patients in clinically indicated situations. There is strong support for developing guidelines for pet use in this patient population.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".