Benefit of determining [-2]proPSA levels in the differential diagnosis of prostate cancer
Bibliographic record
Abstract
Cl:Clem studie je zjistit, zda stanoven [-2]proPSA a vpoet Prostate Health Indexu (PHI) zlep celkovou senzitivitu a specificitu v porovnn s tradin pouvanmi markery (PSA a freePSA) a navrhnout optimln cut-off pro PHI v diferenciln diagnostickm postupu asn detekce karcinomu prostaty (KP).Metodika:U 76 pacient s podezenm na KP a indikovanch k biopsii prostaty byla stanovena hladina celkovho PSA, freePSA, [-2]proPSA, vypotn pomr %freePSA a Prostate Health Index (PHI). Biomarkery se stanovovaly chemiluminiscenn metodou na pstroji Dxl 800 (Beckman Coulter, USA). Statistick vyhodnocen bylo provedeno za vyuit software SAS verze 9.2.Vsledky:Zjistili jsme statisticky vznamn lep hodnoty plochy pod ROC kivkou (AUC) jak pro samotn [-2]proPSA (0,77), tak pedevm pro PHI (0,88) v porovnn s tPSA (0,59) a %freePSA (0,61). dn z nemocnch v naem souboru s biopticky ovenm KP neml PHI ni ne 40.Zvr:Stanoven [-2]proPSA a z nj odvozen hodnota PHI vznamn pispv k zpesnn diferenciln diagnostickho procesu mezi BPH a karcinomem prostaty. Cut-off pro PHI > 40 se edou znou 30-40 je podle naich dosavadnch zkuenost optimln pro vyuit v rutinn praxi pro asnou detekci KP.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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".