Sources of bias in non-randomized comparative studies of surgical procedures
Bibliographic record
Abstract
Introduction Although non randomized comparative studies provide weak evidence for the effectiveness of health interventions, the surgical literature is dominated by these studies. Non randomized studies are prone to selection and measurement biases that exaggerate estimates of the effectiveness of surgical procedures. We sought to quantify the extent of bias associated with characteristics of non randomized studies of surgical procedures. Methods We identified English language studies comparing laparoscopic-assisted and conventional surgery for colon cancer that estimated surgical complications as an outcome measure. A single reviewer determined study eligibility and extracted the data. Subgroup meta-analyses for five study characteristics were performed using R. Summary odds ratios (ORs) and 95% confidence intervals (95% CIs) were estimated using random-effects models. Results 155 comparative studies were identified from 6,261 abstracts. Sixty-three studies that provided an estimate of surgical complications were included. The summary OR for surgical complications associated with laparoscopic-assisted surgery in 21 randomized controlled trials was 0.76 (95% CI 0.62-0.94). The summary OR for surgical complications associated with laparoscopic-assisted surgery in 42 non randomized studies was 0.70 (95% CI 0.64-0.76). Studies with consecutively recruited controls and studies with matched controls estimated a larger benefit of laparoscopic-assisted surgery on complications than studies without these characteristics (see Table). Studies with concurrent controls and systematic assessment of outcomes estimated smaller benefits of laparoscopic-assisted surgery.Characteristics of non randomized studies (n=42)Characteristic presentCharacteristic absentOR ⁎ 95% CIOR ⁎ 95% CIProspective data collection0.670.60-0.760.680.52-0.89Consecutive recruitment of patients0.620.52-0.740.740.66-0.82Concurrent (vs historical) controls0.700.64-0.760.610.22-1.63Matching of groups0.520.35-0.780.710.66-0.78Systematic outcome assessment0.760.72-0.800.600.49-0.74⁎Favoring laparoscopic-assisted surgery Conclusions Among non randomized studies comparing surgical complications after laparoscopic-assisted and conventional surgery for colon cancer, use of matched controls is strongly associated with exaggerated estimates of safety.
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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 | 0.494 | 0.740 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.014 | 0.013 |
| Bibliometrics | 0.019 | 0.023 |
| Science and technology studies | 0.002 | 0.008 |
| Scholarly communication | 0.010 | 0.007 |
| Open science | 0.007 | 0.006 |
| Research integrity | 0.007 | 0.004 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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; the direct Gemma label and the distilled Codex classifier 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".