U.S. Preventive Services Task Force (USPSTF) recommendations on PSA screening (PSAS) for prostate cancer (PC): Are they justified?
Bibliographic record
Abstract
e12535 Background: PSAS has been debated since the Amer Can Soc recommended it in 1992 without data from randomized trials (RTs). Recent RT reports indicate that PSAS does not clearly reduce PC mortality (PCM). In Oct 2011, the USPSTF recommended against PSAS. Does the evidence support this position? Methods: Quebec Trial (QT) randomized 46,193 men 45-80 yrs 2:1 in 1988. Experimental group (EG) was invited for annual PSAS while control group (CG) was not invited. PLCO (Prostate-Lung-Colon-Ovary) randomized 76,693 men 55-74 yrs to annual PSAS or usual care starting in 1993. ERSPC (European study) randomized 162,243 men 55-69 yrs to EG invited to PSAS q4 yrs or CG not invited starting in 1994. Results: QT investigators reported in 1998 that PSAS reduced PCM. The problem was poor compliance with PSAS invitation in QT. Of 30,956 EG, 7,155 (23%) accepted. Of 15,237 CG, 982 (6%) underwent PSAS. Of 8,137 screened (SC), there were 5 PC deaths compared to 137 among 38,056 unSC (RR=0.17; 95% CI: 0.07-0.42). However, this analysis ignores the randomization. Intent to treat (ITT) analysis reveals no PCM reduction (RR=1.11; CI: 0.78-1.59). Selection bias did not account for lower PCM in SC vs unSC. In PLCO, there was no PCM advantage (RR=1.09; CI: 0.87-1.36). However, contamination was high; 72% of CG had PSAS. In ERSPC, there was a reduction in PCM (RR=0.79; CI: 0.69-0.92). Staging of SC detected PC was favorable. In PLCO & ERSPC, increased low/intermediate risk PCs in EGs reflect some overdiagnosis. However, there were significant reductions in high risk or metastatic PC, a hallmark of effective screening. In QT, no pt had distant metastases on repeat PSAS. In PLCO, 10-yr PC survival was ≈94% in both EG & CG. Conclusions: USPSTF recommendations against PSAS are not justified. While PCM comparisons by ITT do not show that PSAS clearly saves lives, ITT analyses are biased due to compliance or contamination. Conversely, RTs demonstrate that PSAS reduces high-risk and metastatic PC. From a population perspective, there has been a dramatic 42% reduction in PCM in US between 1991-2005, largely the result of our "national experiment" in which PSAS was widely introduced. If USPSTF guidelines are implemented, PCM will likely rise in US.
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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 | 0.070 | 0.234 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
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".