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. 2012 Aug 16;367(7):595-605.
doi: 10.1056/NEJMoa1201637.

Quality-of-life effects of prostate-specific antigen screening

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Quality-of-life effects of prostate-specific antigen screening

Eveline A M Heijnsdijk et al. N Engl J Med. .

Abstract

Background: After 11 years of follow-up, the European Randomized Study of Screening for Prostate Cancer (ERSPC) reported a 29% reduction in prostate-cancer mortality among men who underwent screening for prostate-specific antigen (PSA) levels. However, the extent to which harms to quality of life resulting from overdiagnosis and treatment counterbalance this benefit is uncertain.

Methods: On the basis of ERSPC follow-up data, we used Microsimulation Screening Analysis (MISCAN) to predict the number of prostate cancers, treatments, deaths, and quality-adjusted life-years (QALYs) gained after the introduction of PSA screening. Various screening strategies, efficacies, and quality-of-life assumptions were modeled.

Results: Per 1000 men of all ages who were followed for their entire life span, we predicted that annual screening of men between the ages of 55 and 69 years would result in nine fewer deaths from prostate cancer (28% reduction), 14 fewer men receiving palliative therapy (35% reduction), and a total of 73 life-years gained (average, 8.4 years per prostate-cancer death avoided). The number of QALYs that were gained was 56 (range, -21 to 97), a reduction of 23% from unadjusted life-years gained. To prevent one prostate-cancer death, 98 men would need to be screened and 5 cancers would need to be detected. Screening of all men between the ages of 55 and 74 would result in more life-years gained (82) but the same number of QALYs (56).

Conclusions: The benefit of PSA screening was diminished by loss of QALYs owing to postdiagnosis long-term effects. Longer follow-up data from both the ERSPC and quality-of-life analyses are essential before universal recommendations regarding screening can be made. (Funded by the Netherlands Organization for Health Research and Development and others.).

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Figures

Figure 1
Figure 1. Effect of various modeling assumptions on QALYs gained in comparison with the base model (56 QALYs gained)
The assumptions are: 1) no overdiagnosis, 2) screen attendance of 50% and 100%, 3) all unfavorable and favorable utility estimates, 4) utility estimate of 0.93 and 1 for the life-time post-recovery period, 5) utility estimate of 0.86 and 0.24 for palliative therapy, and 6) the utility estimates for the post-recovery period (0.95) and palliative therapy (0.6) as used in the base model combined with the unfavorable and favorable utility estimates of all other health states.

Comment in

References

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