Perceived impact on clinical practice and logistical issues in clinical management surveys of cancer: Australian experience
Bibliographic record
Abstract
BACKGROUND: In September 2004, 28 published and 17 ongoing clinical management surveys (CMS) of cancer in Australia were identified, describing the clinical management of representative series of cancer patients. The present study assessed the perceived influence of these on clinical practice and the logistical issues involved in conducting a CMS. METHODS AND MATERIALS: Questionnaire sent to a key clinical investigator in each survey. RESULTS: For the 28 published CMS, respondents (response rate 54%) reported that the CMS were influential in half or more of subsequent changes in the development or implementation of standard protocols, increasing specialist involvement in clinical trials, reducing variability in practice, and providing informed choice for patients. The surveys were regarded as influential in a third to half of noted changes in the use of evidence-based treatments, multidisciplinary care, and standardised collection of data. For CMS in progress, respondents (response rate 65%) reported on objectives and logistical issues, with the need for multiple ethical approvals emerging as a major issue. CONCLUSION: CMS of cancer have played a modest but important role in stimulating and supporting improvements in clinical care in Australia. Many Australian surveys have been large and population-based and with high response rates. The recent introduction of a requirement for patient consent by some (but not all) ethical committees greatly increases the difficulties and costs of such surveys.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.073 | 0.095 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".