Diagnostic accuracy of tests for lymph node status in primary cervical cancer: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Lymph node status is the key to determining the prognosis and treatment of cervical cancer. However, it cannot be assessed clinically, and testing for nodal metastasis is controversial. We sought to systematically review the diagnostic accuracy literature on sentinel node biopsy, positron emission tomography, magnetic resonance imaging and computed tomography to evaluate the accuracy of each index test in determining lymph node status in patients with cervical cancer. METHODS: We searched MEDLINE (1966-2006), EMBASE (1980-2006), Medion (1980-2006) and the Cochrane library (Issue 2, 2006) for relevant articles. We also manually searched the reference lists from primary articles and reviews, and we contacted experts in the field for conference abstracts and unpublished studies. We performed random-effects meta-analysis of accuracy indices, and we performed meta-regression analysis to test the effect of study quality on diagnostic accuracy and to identify other sources of heterogeneity. RESULTS: We included 72 relevant primary studies, involving a total of 5042 women, in our analysis. We found that, in determining lymph node status, sentinel node biopsy had a pooled positive likelihood ratio of 40.8 (95% confidence interval [CI] 24.6-67.6) and a pooled negative likelihood ratio of 0.18 (95% CI 0.14-0.24). The pooled positive likelihood ratios (and 95% CI) were 15.3 (7.9-29.6) for positron emission tomography, 6.4 (4.9-8.3) for magnetic resonance imaging and 4.3 (3.0-6.2) for computed tomography. The pooled negative likelihood ratios (and 95% CIs) were 0.27 (0.11-0.66) for positron emission tomography, 0.50 (0.39-0.64) for magnetic resonance imaging and 0.58 (0.48-0.70) for computed tomography. Using a 27% pretest probability of lymph node metastasis among all cases (regardless of stage), we found that a positive sentinel node biopsy result increased post-test probability to 94% (95% CI 90%-96%), whereas a positive finding on positron emission tomography increased it to 85% (75%-92%). INTERPRETATION: Sentinel node biopsy has greater accuracy in determining lymph node status among women with primary cervical cancer than current commonly used imaging methods.
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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 | 0.040 | 0.127 |
| Meta-epidemiology (narrow) | 0.004 | 0.003 |
| Meta-epidemiology (broad) | 0.023 | 0.056 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| 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".