A systematic review and meta‐analysis of placebo effect in clinical trials on chronic prostatitis/chronic pelvic pain syndrome
Bibliographic record
Abstract
BACKGROUND: It is a common practice to control efficacy of pharmacological treatment with a placebo group. However, placebo itself may affect subjective and even objective results. The purpose of this study was to evaluate the placebo effect on symptoms of CP/CPPS to improve future clinical trials. METHODS: A search at three databases (Scopus, MEDLINE, and Web of Science) was conducted to identify double-blind placebo-controlled clinical trials on the treatment of CP/CPPS published until April 2021. The primary outcome - National Institutes of Health Chronic Prostatitis Symptom Index (NIH-CPSI) score. SECONDARY OUTCOMES: Qmax, PVR, IPSS, and prostate volume. RESULTS: A total of 3502 studies were identified. Placebo arms of 42 articles (5512 patients, median 31 patients) were included in the systematic review. Systematic review identified positive changes in the primary endpoint, meta-analysis of 10 articles found that NIH-CPSI total score results were significantly influenced by placebo, mean difference -4.2 (95% confidence interval [CI]: -6.31, -2.09). Mean difference of NIH-CPSI pain domain was -2.31 (95% CI: -3.4, -1.21), urinary domain -1.12 (95% CI: -1.62, -0.62), quality of life domain -1.67 (95% CI: -2.38, -0.96); p < 0.001 for all. In case of the objective indicator - Qmax, there were three articles included in the meta-analysis. Qmax mean change from baseline was 0.68 (95% CI: -0.85, 2.22, p = 0.38). Systematic review showed no significant changes in pain, measured by VAS or other scores, IPSS and PVR. CONCLUSIONS: Placebo significantly affected the subjective parameters (NIH-CPSI) and limitedly affected various other measurements of pain (visual analog scale, McGill pain questionnaire). There was no long-term effect on IPSS and objective measurements (Qmax, PVR). This study can be used in further clinical trials to develop general rules of CPPS treatment assessment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.023 | 0.059 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.025 | 0.030 |
| Bibliometrics | 0.008 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".