Bibliographic record
Abstract
Urologists have had their "reset" button pushed by the recent USPSTF draft recommendation against PSA screening.Part of the concern relates to the limitations and morbidity of prostate biopsy.In a population subject to PSA screening, prostate biopsies are negative in most cases, have a negative predictive value of only 75%, and are associated with a significant risk of urosepsis requiring hospitalization.A major unmet need is to reduce the number of patients requiring biopsy and the number of cores required without reducing the diagnosis of clinically significant prostate cancer.In this regard, McCormack and colleagues compare the cancer detection rate and complication rate from TRUS biopsy using 18G and 16G needles. 1 The rationale was that larger needles might increase the detection rate.One group had core biopsies taken with both needles; the other, with 18G needles only.There were about 100 patients per group.There was no difference in either outcome; 4% of patients in each group had febrile urosepsis.Notwithstanding the results, I will continue to use the smallest needle available for TRUS biopsies.It is logical that the larger the needle, the greater the bacterial load carried from the rectum to the prostate, and the greater the risk of complications.The study was underpowered to detect a 25% relative increase in urosepsis rate with high confidence levels.Further, evidence regarding MRIs in patients with "missed" cancers suggests that it is location, location, location rather than the size of the needle that is the problem in these patients.I'd bet on the increased use of multiparametric MRI and biomarkers rather than larger needles as the solution to the biopsy conundrum.Radiation oncologists are bullish on the role of adjuvant therapy for patients with PSMs after radical prostatectomy.Three randomized studies suggest a benefit of adjuvant radiation in this setting.However, many urologists elect to follow patients and treat with early salvage therapy.The selective approach avoids overtreatment of those not destined to progress.Nonetheless, it is clear from many studies that for patients who have residual local disease, the earlier the radiation therapy is given the greater the likelihood of durable response.Given the trade-offs, diversity of practice is not surprising.Thus, the study by Tyldesley and colleagues is shocking. 2Only 1.1% of patients with PSMs received adjuvant radiation therapy.Only 23% of eligible patients saw a radiation oncologist within 6 months of surgery.The authors conclude that "We encourage all urologists to consider early referral (within 6 months of surgery) to a radiation oncologist for consideration of adjuvant radiotherapy in the setting of high-risk features."Many patients declare themselves at very high risk for recurrence.Such patients should be referred for adjuvant radiation.Further, in the face of uncertainty, the RADICALS trial comparing adjuvant to early salvage radiation warrants our support.Finally, the data indicate that only 25/230 patients seen postoperatively by radiation oncologists actually received adjuvant therapy.This suggests that even radiation oncologists are resistant to the use of adjuvant radiation therapy in the setting of high-risk features!We welcome the paper by Dr. Zhou and colleagues from Shanghai analyzing the quality and quantity of scientific publications in urology and nephrology from China. 3 Links between China and Canada have been formalized under the aegis of the Norman Bethune Urological Society-CUA.We look forward to many more submissions from our Chinese colleagues.
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 | 0.003 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 0.006 |
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".