Abstract 749: Plasma insulin-like growth factor 1-related biomarkers and risk of lethal prostate cancer
Notice bibliographique
Résumé
Abstract Background Experimental and epidemiologic evidence supports the role of plasma IGF-1 and risk of prostate cancer. About 5% of IGF-1 circulates in a free or bioavailable form, and is only weakly correlated with total IGF-1; we hypothesized that higher levels of free IGF-1 would be associated with risk of lethal prostate cancer. Methods Lethal prostate cancer was defined as fatal prostate cancer plus metastatic prostate cancer. Non-lethal prostate cancer was defined as cases in which the men remained free of known metastases for at least eight years. Using prospectively collected samples in a nested design, we identified 434 lethal cases and 524 men with non-lethal prostate cancer in two prospective cohorts: the Physicians' Health Study (mean years of follow-up 33.2) and the Health Professionals Follow-up Study (mean years of follow-up 18.5). Circulating levels in prediagnostic plasma samples were assayed for IGF-1-related biomarkers, including free and total IGF-1, acid labile subunit (ALS), pregnancy-associated plasma protein A (PAPP-A, a protease that cleaves the IGF complex), intact IGF binding protein 4 (IGFBP-4), and total IGFBP-4, with risk of lethal prostate cancer. We estimated odds ratios (ORs) and corresponding 95% confidence intervals (CI) for the associations between IGF-1-related biomarkers (in quartiles) and lethal prostate cancer using unconditional logistic regression models adjusted for age, height, weight, and body mass index. Subgroup analyses were conducted by time from blood draw to diagnosis, and tumor biomarkers, ERG as a marker of the TMPRSS2:ERG fusion, phosphatase and tensin homolog (PTEN) loss, and IGF-1 receptor (IGF1R) protein expression. Results We observed no significant association between free IGF-1 and lethal prostate cancer (pooled adjusted OR for the highest versus lowest group 0.93, 95% CI 0.64 to 1.35) after adjusting for potential covariates. However, men in the highest quartile of PAPP-A levels had 43% higher odds of developing lethal prostate cancer (pooled adjusted OR 1.43, 95% CI 1.05 to 1.95) compared to men in the lowest three quartiles. The positive association between PAPP-A and lethal prostate cancer was present among men without PTEN loss, but not among those with (P for interaction = 0.002). There were no significant differences across the two cohorts (P for heterogeneity > 0.05 for all) and no significant associations were observed between other plasma biomarkers and lethal prostate cancer. Conclusions We found no significant association between free IGF-1 and lethal prostate cancer, but provide suggestive evidence that higher PAPP-A levels are associated with an increased risk of developing lethal prostate cancer. This observation merits testing in other cohorts. Citation Format: Chaoran Ma, Ye Wang, Lorelei A. Mucci, Meir J. Stampfer, Michael Pollak, Kathryn L. Penney. Plasma insulin-like growth factor 1-related biomarkers and risk of lethal prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 749.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».