Optimal treatment of intermediate‐risk prostate carcinoma with radiotherapy
Bibliographic record
Abstract
The clinical heterogeneity of intermediate-risk prostate carcinoma presents a challenge to urologic oncology in terms of prognosis and management. There is controversy regarding whether patients with intermediate-risk prostate carcinoma should be treated with dose-escalated external beam radiotherapy (EBRT) (e.g., doses > 74 gray [Gy]), or conventional-dose EBRT (e.g., doses < 74 Gy) combined with androgen deprivation (AD). Data for this review were identified through searches for articles in MEDLINE and in conference proceedings, indexed from 1966 to 2004. Currently, the intermediate-risk prostate carcinoma grouping is defined on the basis of prostate-specific antigen (PSA), tumor classification (T classification), and Gleason score. Emerging evidence suggests that additional prognostic information may be derived from the percentage of positive core needle biopsies at the time of diagnosis and/or from the pretreatment PSA doubling time. Novel prognostic biomarkers include protein expression relating to cell cycle control, cell death, DNA repair, and intracellular signal transduction. Preclinical data support dose escalation or combined AD with radiation as a means to increase prostate carcinoma cell kill. There is Level I evidence that patients with intermediate-risk prostate carcinoma benefit from dose-escalated EBRT or AD plus conventional-dose EBRT. However, clinical evidence is lacking to support the uniform use of AD plus dose-escalated EBRT. Patients in the intermediate-risk group should be entered into well designed, randomized clinical trials of dose-escalated EBRT and AD with sufficient power to address biochemical failure and cause-specific survival endpoints. These studies should be stratified by novel prognostic markers and accompanied by strong translational endpoints to address clinical heterogeneity and to allow for individualized treatment.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".