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Articles by G. J Mann
Total Records ( 2 ) for G. J Mann
  K Howard , A Barratt , G. J Mann and M. I. Patel
 

Background  Information is needed to aid individual decision making about prostate-specific antigen (PSA) screening.

Methods  We aimed to provide such information for men aged 40, 50, 60, and 70 years at low, moderate, and high risk for prostate cancer. A Markov model compared patients with vs without annual PSA screening using a 20% relative risk (RR) reduction (RR = 0.8) in prostate cancer mortality as a best-case scenario. The model estimated numbers of biopsies, prostate cancers, and deaths from prostate cancer per 1000 men over 10 years and cumulated to age 85 years.

Results  Benefits and harms vary substantially with age and familial risk. Using 60-year-old men with low risk as an example, of 1000 men screened annually, we estimate that 115 men will undergo biopsy triggered by an abnormal PSA screen result and that 53 men will be diagnosed as having prostate cancer over 10 years compared with 23 men diagnosed as having prostate cancer among 1000 unscreened men. Among screened men, 3.5 will die of prostate cancer over 10 years compared with 4.4 deaths in unscreened men. For 1000 men screened from 40 to 69 years of age, there will be 27.9 prostate cancer deaths and 639.5 deaths overall by age 85 years compared with 29.9 prostate cancer deaths and 640.4 deaths overall in unscreened men. Higher-risk men have more prostate cancer deaths averted but also more prostate cancers diagnosed and related harms.

Conclusions  Men should be informed of the likely benefits and harms of PSA screening. These estimates can be used to support individual decision making.

  F Demenais , H Mohamdi , V Chaudru , A. M Goldstein , J. A Newton Bishop , D. T Bishop , P. A Kanetsky , N. K Hayward , E Gillanders , D. E Elder , M. F Avril , E Azizi , P van Belle , W Bergman , G Bianchi Scarra , B Bressac de Paillerets , D Calista , C Carrera , J Hansson , M Harland , D Hogg , V Hoiom , E. A Holland , C Ingvar , M. T Landi , J. M Lang , R. M Mackie , G. J Mann , M. E Ming , C. J Njauw , H Olsson , J Palmer , L Pastorino , S Puig , J Randerson Moor , M Stark , H Tsao , M. A Tucker , P van der Velden , X. R Yang , N Gruis and and the Melanoma Genetics Consortium
  Background

Carrying the cyclin-dependent kinase inhibitor 2A (CDKN2A) germline mutations is associated with a high risk for melanoma. Penetrance of CDKN2A mutations is modified by pigmentation characteristics, nevus phenotypes, and some variants of the melanocortin-1 receptor gene (MC1R), which is known to have a role in the pigmentation process. However, investigation of the associations of both MC1R variants and host phenotypes with melanoma risk has been limited.

Methods

We included 815 CDKN2A mutation carriers (473 affected, and 342 unaffected, with melanoma) from 186 families from 15 centers in Europe, North America, and Australia who participated in the Melanoma Genetics Consortium. In this family-based study, we assessed the associations of the four most frequent MC1R variants (V60L, V92M, R151C, and R160W) and the number of variants (1, ≥2 variants), alone or jointly with the host phenotypes (hair color, propensity to sunburn, and number of nevi), with melanoma risk in CDKN2A mutation carriers. These associations were estimated and tested using generalized estimating equations. All statistical tests were two-sided.

Results

Carrying any one of the four most frequent MC1R variants (V60L, V92M, R151C, R160W) in CDKN2A mutation carriers was associated with a statistically significantly increased risk for melanoma across all continents (1.24 x 10–6P ≤ .0007). A consistent pattern of increase in melanoma risk was also associated with increase in number of MC1R variants. The risk of melanoma associated with at least two MC1R variants was 2.6-fold higher than the risk associated with only one variant (odds ratio = 5.83 [95% confidence interval = 3.60 to 9.46] vs 2.25 [95% confidence interval = 1.44 to 3.52]; Ptrend = 1.86 x 10–8). The joint analysis of MC1R variants and host phenotypes showed statistically significant associations of melanoma risk, together with MC1R variants (.0001 ≤ P ≤ .04), hair color (.006 ≤ P ≤ .06), and number of nevi (6.9 x 10–6P ≤ .02).

Conclusion

Results show that MC1R variants, hair color, and number of nevi were jointly associated with melanoma risk in CDKN2A mutation carriers. This joint association may have important consequences for risk assessments in familial settings.

 
 
 
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