Breast Cancer Screening: The Effect of Self Selection for Screening on Comparisons of Randomised Controlled Trials

Richardson, Ann; Wells, J Elisabeth

doi:10.1177/096914139700400106

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…As in other programmes where SDRs have been calculated, our calculations have not taken into account the likelihood that there is self-selection of high-risk (or low-risk) women for screening. 12 It has been shown that self-selection occurred in some of the randomised controlled trials, and also that there was self-selection of high-risk women for screening in the NHSBSP. 13 Self-selection could affect invasive breast cancer detection rates and SDRs, particularly with lower coverage than that achieved in the Swedish Two-County trial.…”

Section: Discussionmentioning

confidence: 99%

Breast cancer detection rates, and standardised detection ratios for prevalence screening in the New Zealand breast cancer screening programme

et al. 2004

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In the first two years of the national programme, detection to expected incidence ratios were less than 3.0, and the SDR results were below 1.0. It may be unrealistic to expect new screening programmes to achieve SDRs of 1.0 immediately. At a similar stage, the UK National Health Service Breast Cancer Screening Programme (NHSBSP) also reported SDRs of less than 1.0 and therefore lower than expected cancer detection rates compared with the Swedish Two-County trial. An encouraging finding was that SDRs in five of the six screening regions improved in the second year of the New Zealand screening programme.

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Section: Discussionmentioning

confidence: 99%

Breast cancer detection rates, and standardised detection ratios for prevalence screening in the New Zealand breast cancer screening programme

et al. 2004

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“…Firstly, the following formula is used to adjust participation rates for self selection. 5 If m n is the mortality in the nonattenders, and m c is the mortality in the control group, in the absence of a screening programme the expected mortality in the intervention group would be E(m u ) = pm h + (1-p)m n Where E(m u ) is the expected mortality in the intervention group had there been no screening programme, m h is the hypothetical mortality rate in the attenders had there been no screening programme, and p is the proportion of the intervention group which attended screening.…”

mentioning

confidence: 99%

Screening and the number needed to treat

Richardson

2001

J Med Screen

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The NNT calculations may make population based screening programmes seem expensive and inefficient compared with other interventions. A new measure, the number needed to be screened (NNBS), which takes into account the participation rate adjusted for selection, may be more appropriate, especially when comparing screening programmes with disparate participation rates, or when comparing screening with other interventions.

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“…The volunteer effect has been studied extensively in screening trials for cancer of the breast, colon-rectum and prostate [1–3], but it has been scarcely investigated in the context of screening for lung cancer (LC). The Johns Hopkins Lung Project first documented that the LC mortality of volunteers screened by chest X-rays (CXR) was significantly higher than expected on the basis of two large population studies, namely the Veterans Study [observed/expected LC mortality ratio 1.72; 95% confidence interval (CI) 1.28–2.18] and the American Cancer Society Study (observed/expected LC mortality ratio 1.46; 95% CI 1.09–1.83) [4].…”

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Volunteer effect and compromised randomization in the Mayo Project of screening for lung cancer

et al. 2010

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It has been confirmed recently that the volunteer effect in lung cancer screening is characterized by higher lung cancer mortality risk in self-selected screening participants. The Mayo Lung Project, the most influential trial of screening for lung cancer ever completed, was conducted in nonvolunteer Mayo Clinic outpatients, with a peculiar study design that rendered the randomization vulnerable to the volunteer effect. Of all nonvolunteers randomized in the Mayo Lung Project, only those allocated in the screened group were asked consent to participate in the trial. The final Mayo Lung Project report stated that 655 randomized nonvolunteers refused screening and were excluded from the study, thus documenting violation of the rule that no selection should occur after randomization. The long-term follow-up of the Mayo Lung Project showed an enigmatic result which has never been explained: the lung cancer mortality was 13% higher in the screening intervention group than in the control group [4.4 (95% CI 3.9–4.9) vs. 3.9 (95% CI 3.5–4.4) per 1,000 person-years; P = 0.09]. Such overrepresented mortality is consistent with the volunteer effect and supports the concept that the Mayo Lung Project randomization was compromised by the post-randomization self-selection of participant nonvolunteers.

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Breast Cancer Screening: The Effect of Self Selection for Screening on Comparisons of Randomised Controlled Trials

Cited by 6 publications

References 6 publications

Breast cancer detection rates, and standardised detection ratios for prevalence screening in the New Zealand breast cancer screening programme

Breast cancer detection rates, and standardised detection ratios for prevalence screening in the New Zealand breast cancer screening programme

Screening and the number needed to treat

Volunteer effect and compromised randomization in the Mayo Project of screening for lung cancer

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