Home > Publications database > Coffee Intake, Caffeine Metabolism Genotype, and Survival Among Men with Prostate Cancer. > print |
001 | 181396 | ||
005 | 20240229145646.0 | ||
024 | 7 | _ | |a 10.1016/j.euo.2022.07.008 |2 doi |
024 | 7 | _ | |a pmid:35995710 |2 pmid |
024 | 7 | _ | |a altmetric:134766297 |2 altmetric |
037 | _ | _ | |a DKFZ-2022-01964 |
041 | _ | _ | |a English |
082 | _ | _ | |a 610 |
100 | 1 | _ | |a Gregg, Justin R |b 0 |
245 | _ | _ | |a Coffee Intake, Caffeine Metabolism Genotype, and Survival Among Men with Prostate Cancer. |
260 | _ | _ | |a Amsterdam |c 2023 |b Elsevier |
336 | 7 | _ | |a article |2 DRIVER |
336 | 7 | _ | |a Output Types/Journal article |2 DataCite |
336 | 7 | _ | |a Journal Article |b journal |m journal |0 PUB:(DE-HGF)16 |s 1687350577_6280 |2 PUB:(DE-HGF) |
336 | 7 | _ | |a ARTICLE |2 BibTeX |
336 | 7 | _ | |a JOURNAL_ARTICLE |2 ORCID |
336 | 7 | _ | |a Journal Article |0 0 |2 EndNote |
500 | _ | _ | |a 2023 Jun;6(3):282-288 |
520 | _ | _ | |a Coffee intake may lower prostate cancer risk and progression, but postdiagnosis outcomes by caffeine metabolism genotype are not well characterized.To evaluate associations between coffee intake, caffeine metabolism genotype, and survival in a large, multicenter study of men with prostate cancer.Data from The PRACTICAL Consortium database for 5727 men with prostate cancer from seven US, Australian, and European studies were included. The cases included had data available for the CYP1A2 -163C>A rs762551 single-nucleotide variant associated with caffeine metabolism, coffee intake, and >6 mo of follow-up.Multivariable-adjusted Cox proportional hazards models across pooled patient-level data were used to compare the effect of coffee intake (categorized as low [reference], high, or none/very low) in relation to overall survival (OS) and prostate cancer-specific survival (PCSS), with stratified analyses conducted by clinical disease risk and genotype.High coffee intake appeared to be associated with longer PCSS (hazard ratio [HR] 0.85, 95% confidence interval [CI] 0.68-1.08; p = 0.18) and OS (HR 0.90, 95% CI 0.77-1.07; p = 0.24), although results were not statistically significant. In the group with clinically localized disease, high coffee intake was associated with longer PCSS (HR 0.66, 95% CI 0.44-0.98; p = 0.040), with comparable results for the group with advanced disease (HR 0.92, 95% CI 0.69-1.23; p = 0.6). High coffee intake was associated with longer PCSS among men with the CYP1A2 AA (HR 0.67, 95% CI 0.49-0.93; p = 0.017) but not the AC/CC genotype (p = 0.8); an interaction was detected (p = 0.042). No associations with OS were observed in subgroup analyses (p > 0.05). Limitations include the nominal statistical significance and residual confounding.Coffee intake was associated with longer PCSS among men with a CYP1A2 -163AA (*1F/*1F) genotype, a finding that will require further replication.It is likely that coffee intake is associated with longer prostate cancer-specific survival in certain groups, but more research is needed to fully understand which men may benefit and why. |
536 | _ | _ | |a 313 - Krebsrisikofaktoren und Prävention (POF4-313) |0 G:(DE-HGF)POF4-313 |c POF4-313 |f POF IV |x 0 |
588 | _ | _ | |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de |
650 | _ | 7 | |a Caffeine |2 Other |
650 | _ | 7 | |a Coffee |2 Other |
650 | _ | 7 | |a Genetic variation |2 Other |
650 | _ | 7 | |a Mortality |2 Other |
650 | _ | 7 | |a Prostatic neoplasms |2 Other |
700 | 1 | _ | |a Kim, Jeri |b 1 |
700 | 1 | _ | |a Logothetis, Christopher |b 2 |
700 | 1 | _ | |a Hanash, Sam |b 3 |
700 | 1 | _ | |a Zhang, Xiaotao |b 4 |
700 | 1 | _ | |a Manyam, Ganiraju |b 5 |
700 | 1 | _ | |a Muir, Kenneth |b 6 |
700 | 1 | _ | |a Group, UKGPCS Collaborative |b 7 |e Collaboration Author |
700 | 1 | _ | |a Giles, Graham G |b 8 |
700 | 1 | _ | |a Stanford, Janet L |b 9 |
700 | 1 | _ | |a Berndt, Sonja I |b 10 |
700 | 1 | _ | |a Kogevinas, Manolis |b 11 |
700 | 1 | _ | |a Brenner, Hermann |0 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |b 12 |u dkfz |
700 | 1 | _ | |a Eeles, Rosalind A |b 13 |
700 | 1 | _ | |a Consortium, PRACTICAL |b 14 |e Collaboration Author |
700 | 1 | _ | |a Wei, Peng |b 15 |
700 | 1 | _ | |a Daniel, Carrie R |b 16 |
773 | _ | _ | |a 10.1016/j.euo.2022.07.008 |g p. S2588931122001389 |0 PERI:(DE-600)2945338-0 |n 3 |p 282-288 |t European urology oncology |v 6 |y 2023 |x 2588-9311 |
909 | C | O | |p VDB |o oai:inrepo02.dkfz.de:181396 |
910 | 1 | _ | |a Deutsches Krebsforschungszentrum |0 I:(DE-588b)2036810-0 |k DKFZ |b 12 |6 P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2 |
913 | 1 | _ | |a DE-HGF |b Gesundheit |l Krebsforschung |1 G:(DE-HGF)POF4-310 |0 G:(DE-HGF)POF4-313 |3 G:(DE-HGF)POF4 |2 G:(DE-HGF)POF4-300 |4 G:(DE-HGF)POF |v Krebsrisikofaktoren und Prävention |x 0 |
914 | 1 | _ | |y 2022 |
915 | _ | _ | |a JCR |0 StatID:(DE-HGF)0100 |2 StatID |b EUR UROL ONCOL : 2022 |d 2023-08-25 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0200 |2 StatID |b SCOPUS |d 2023-08-25 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0300 |2 StatID |b Medline |d 2023-08-25 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0199 |2 StatID |b Clarivate Analytics Master Journal List |d 2023-08-25 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)0150 |2 StatID |b Web of Science Core Collection |d 2023-08-25 |
915 | _ | _ | |a DBCoverage |0 StatID:(DE-HGF)1110 |2 StatID |b Current Contents - Clinical Medicine |d 2023-08-25 |
915 | _ | _ | |a IF >= 5 |0 StatID:(DE-HGF)9905 |2 StatID |b EUR UROL ONCOL : 2022 |d 2023-08-25 |
920 | 1 | _ | |0 I:(DE-He78)C070-20160331 |k C070 |l C070 Klinische Epidemiologie und Alternf. |x 0 |
920 | 1 | _ | |0 I:(DE-He78)C120-20160331 |k C120 |l Präventive Onkologie |x 1 |
920 | 1 | _ | |0 I:(DE-He78)HD01-20160331 |k HD01 |l DKTK HD zentral |x 2 |
980 | _ | _ | |a journal |
980 | _ | _ | |a VDB |
980 | _ | _ | |a I:(DE-He78)C070-20160331 |
980 | _ | _ | |a I:(DE-He78)C120-20160331 |
980 | _ | _ | |a I:(DE-He78)HD01-20160331 |
980 | _ | _ | |a UNRESTRICTED |
Library | Collection | CLSMajor | CLSMinor | Language | Author |
---|