Appropriateness of oral drugs for long-term treatment of lower urinary tract symptoms in older persons: results of a systematic literature review and international consensus validation process (LUTS-FORTA 2014)
Bibliographic record
Abstract
AIM: we aimed to systematically review drugs to treat lower urinary tract symptoms (LUTS) regularly used in older persons to classify appropriate and inappropriate drugs based on efficacy, safety and tolerability by using the Fit fOR The Aged (FORTA) classification. METHODS: to evaluate the efficacy, safety and tolerability of drugs used for treatment of LUTS in older persons, a systematic review was performed. Papers on clinical trials and summaries of individual product characteristics were analysed regarding efficacy and safety in older persons (≥65 years). The most frequently used drugs were selected based on current prescription data. An interdisciplinary international expert panel assessed the drugs in a Delphi process. RESULTS: for the 16 drugs included here, a total of 896 citations were identified; of those, only 25 reported clinical trials with explicit data on, or solely performed in older people, underlining the lack of evidence in older people for drug treatment of LUTS. No drug was rated at the FORTA-A-level (indispensable). Only three were assigned to FORTA B (beneficial): dutasteride, fesoterodine and finasteride. The majority was rated FORTA C (questionable): darifenacin, mirabegron, extended release oxybutynin, silodosin, solifenacin, tadalafil, tamsulosin, tolterodine and trospium. FORTA D (avoid) was assigned to alfuzosin, doxazosin, immediate release oxybutynin, propiverine and terazosin. CONCLUSIONS: dutasteride, fesoterodine and finasteride were classified as beneficial in older persons or frail elderly people (FORTA B). For most drugs, in particular those from the group of α-blockers and antimuscarinics, use in this group seems questionable (FORTA C) or should be avoided (FORTA D).
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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 | 0.066 | 0.152 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.011 |
| Bibliometrics | 0.027 | 0.015 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.002 | 0.001 |
| 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".