Bibliographic record
Abstract
去勢抵抗性前立腺がん（CRPC）の治療薬として，『前立腺癌診療ガイドライン2016年版』では，従来から用いられてきたドセタキセルに加え，2014年に登場した化学療法薬のカバジタキセル，CYP17A阻害薬であるアビラテロンおよびアンドロゲン受容体（AR）シグナル伝達路を標的としたAR標的薬であるエンザルタミドの４剤が推奨グレードAで推奨されている。さらに，近い将来，日本においても新たなAR標的薬であるapalutamide，darolutamideの臨床応用が予想されている。このようにCRPCに対して有効な治療選択肢が増える一方，これらの薬剤をどのような患者にどのような順番で投与すればよいのか（逐次療法）についてはコンセンサスが得られていない。そこで，これまでに得られているエビデンスや診療ガイドラインを踏まえ，CRPCの治療の現状や課題，今後の展望について，東邦大学医療センター佐倉病院泌尿器科教授の鈴木先生にお話を伺った。
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".