Management pathway for patients with cervical cancer in the Auckland region 2003-2007
Bibliographic record
Abstract
INTRODUCTION: This review was performed to describe the patient pathway and timelines involved in the treatment of FIGO (International Federation of Gynecology and Obstetrics) stage IB1 to IVA cervical cancer in a New Zealand cancer centre. METHODS: Retrospective audit of women with a new diagnosis of FIGO Stage IB1-IVA cervical cancer in the Auckland/Northland regions between 2003 and 2007. RESULTS: Two hundred and seven patients were identified. Median time from referral to first specialist assessment (FSA) was 10days, from FSA to decision to treat (DTT) 50days and from DTT to start of treatment 26days. Overall median time from referral to start of treatment was 97days. There was no difference in median time from referral to DTT for patients treated with primary surgery (48days) or radiotherapy (47days). On univariate analysis, factors associated with reduced time from referral to start of treatment were less socioeconomic deprivation (P=0.001), shorter time to completion of radiological investigations (P<0.0005) and private FSA (P<0.0005). Only private FSA remained significant on multivariate analysis. The greatest delay in the pathway was between FSA and DTT, encompassing presentation at multidisciplinary meeting, examination under anaesthetic and obtaining radiological investigations. Median overall treatment time (OTT) for patients treated with definitive radiotherapy was 56days and was increased by a median of 3days where there were delays accessing operating theatre time for brachytherapy insertions. CONCLUSION: Overall patient pathway and radiotherapy OTT were longer than optimal, and areas of delay potentially amenable to modification were identified.
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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 | 0.000 | 0.003 |
| 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) | 0.002 | 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".