Staging locally advanced cervical cancer with FIGO 2018 versus FIGO 2008: Impact on overall survival and progression-free survival in the OUTBACK trial (ANZGOG 0902, RTOG 1174, NRG 0274).
Bibliographic record
Abstract
5531 Background: The International Federation of Obstetrics and Gynecology staging system for cervical cancer (FIGO 2008) was revised in 2018 to incorporate lymph node involvement (FIGO 2018). OUTBACK is an international, randomized phase 3 trial of adjuvant chemotherapy versus observation after standard of care treatment with chemoradiation for women with locally advanced cervical cancer. OUTBACK found no benefit from the addition of adjuvant chemotherapy. We evaluated the effects of classifying participants with these 2 staging systems in the OUTBACK trial population. Methods: OUTBACK recruited April 2011 to June 2017 and staged participants according to FIGO 2008. Lymph node status, smoking status, age, race and histological subtype were documented at trial entry as important prognostic factors. We assessed the effects of stage grouping into stage I, II, and III/IVa with FIGO 2008 versus FIGO 2018, on progression-free survival (PFS) and overall survival (OS) at 5 years using Kaplan-Meier estimates, and in univariable proportional-hazards regression analyses, and in multivariable analyses adjusting for important prognostic factors and randomly allocated treatment. Results: All 919 study participants had complete data for staging according to the 2 staging systems and most prognostic factors for adjustment. Among all participants, the 5-year outcomes were PFS = 62% and OS = 72%. Classification according to FIGO 2018 rather than FIGO 2008 yielded higher 5-year PFS and OS in each stage group (see table for numbers of participants, PFS and OS for each stage group). Predictors of PFS in multivariable analysis included squamous vs non-squamous histology (HR 0.71 for FIGO 2008 and 0.74 for FIGO 2018), but not nodal involvement when FIGO 2018 was used. Both staging systems were the only independently significant prognostic factors in both univariable and multivariable analyses (all p < 0.0001) for both PFS and OS. Conclusions: Compared to FIGO 2008, reclassifying pts by FIGO 2018 staging resulted in more pts being classified as stage 3 due to the incorporation of nodal status. Staging locally advanced cervical cancer using FIGO 2018 rather than FIGO 2008 resulted in higher PFS and OS in each stage grouping that reflected stage migration, not a true improvement in outcomes. FIGO stage remains the strongest predictor of overall survival after CRT but survival outcomes by stage in trials using the old vs new staging system are not comparable. Clinical trial information: ACTRN12610000732088. [Table: see text]
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".