Estimating mean sojourn time and screening test sensitivity in breast cancer mammography screening: new results

Weedon‐Fekjær, Harald; Vatten, Lars J.; Aalen, Odd O.; Lindqvist, Bo Henry; Tretli, Steinar

doi:10.1258/096914105775220732

Cited by 37 publications

(57 citation statements)

References 21 publications

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“…Compared to previous studies, the estimation using the data from Swedish Two-County trial was 3.3 years for the same age group [5]. Norwegian Breast Cancer Screening Programme study estimated the MST to be 4 years or below after excluding intraductal carcinomas, adjusting for extra background incidence and correcting for possible bias due to opportunistic screening between screening rounds by using non-linear least-square regression approach for the estimation of a three-state Markov chain model [6]. The data used in the Norwegian study was only from the prevalent screening with a higher proportion of slow-growing tumors in screen-detected cancers compared to the subsequent incidence rounds.…”

Section: Discussionmentioning

confidence: 99%

“…Similar methods have not been applied to evaluation of population-based organized service screening program from which self-selection bias and lead-time bias are inherent. The natural history of breast cancer seems to be heterogeneous across different populations [5,6]. Therefore, it may be worthwhile to evaluate each breast cancer service screening program by elucidating the disease natural history to answer a series of subsidiary questions mentioned above.…”

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confidence: 99%

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Estimation of natural history parameters of breast cancer based on non-randomized organized screening data: subsidiary analysis of effects of inter-screening interval, sensitivity, and attendance rate on reduction of advanced cancer

Hakama

Anttila

et al. 2010

Breast Cancer Res Treat

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-Fang Yen, Nea Malila, et al.. Estimation of natural history parameters of breast cancer based on non-randomized organized screening data: subsidiary analysis of effects of inter-screening interval, sensitivity, and attendance rate on reduction of advanced cancer. Breast Cancer Research and Treatment, Springer Verlag, 2010, 122 (2), pp.553-566. <10.1007/s10549-009-0701-x>. EPIDEMIOLOGYEstimation of natural history parameters of breast cancer based on non-randomized organized screening data: subsidiary analysis of effects of inter-screening interval, sensitivity, and attendance rate on reduction of advanced cancer Abstract Estimating the natural history parameters of breast cancer not only elucidates the disease progression but also make contributions to assessing the impact of interscreening interval, sensitivity, and attendance rate on reducing advanced breast cancer. We applied three-state and five-state Markov models to data on a two-yearly routine mammography screening in Finland between 1988 and 2000. The mean sojourn time (MST) was computed from estimated transition parameters. Computer simulation was implemented to examine the effect of inter-screening interval, sensitivity, and attendance rate on reducing advanced breast cancers. In three-state model, the MST was 2.02 years, and the sensitivity for detecting preclinical breast cancer was 84.83%. In five-state model, the MST was 2.21 years for localized tumor and 0.82 year for non-localized tumor. Annual, biennial, and triennial screening programs can reduce 53, 37, and 28% of advanced cancer. The effectiveness of intensive screening with poor attendance is the same as that of infrequent screening with high attendance rate. We demonstrated how to estimate the natural history parameters using a service screening program and applied these parameters to assess the impact of inter-screening interval, sensitivity, and attendance rate on reducing advanced cancer. The proposed method makes contribution to further costeffectiveness analysis. However, these findings had better be validated by using a further long-term follow-up data.

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Section: Discussionmentioning

confidence: 99%

mentioning

confidence: 99%

Estimation of natural history parameters of breast cancer based on non-randomized organized screening data: subsidiary analysis of effects of inter-screening interval, sensitivity, and attendance rate on reduction of advanced cancer

Hakama

Anttila

et al. 2010

Breast Cancer Res Treat

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“…21,22 Because clinical trial data for Korean women were not available, we simulated the threshold screening schedules for a possible range of b and MST in this study.…”

Section: Discussionmentioning

confidence: 99%

Scheduling mammography screening for the early detection of breast cancer in Korean women

et al. 2007

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Objective To propose an efficient screening schedule for breast cancer among Korean women using the stochastic model in which the age-specific incidence rate was considered. Setting Female breast cancer data in the Korea Central Cancer Registry 2002. Methods The stochastic model was based on the threshold method, in which the schedule is determined by a pre-specified threshold value. The threshold value was defined as the probability of being in a preclinical state of breast cancer at age 40 years. The sensitivity of the mammography was specified as 0.7. Two models for mean sojourn time (MST) in the preclinical state were considered; MSTs for Model I were 2 (ageso50 years), 3 (ages 50-59 years), and 4 years (ages X60 years), and MSTs for Model II were 3, 4, and 5 years for the corresponding age groups. Results The threshold method for Model I generated 19 examinations within the screening ages of 40-69 years. Each screening time was determined at ages 40.0, 41.6, 43.2, 44.8, 46.0, 47.2, 48.4, 49.6, 50.7, 51.7, 52.7, 53.7, 54.7, 56.2, 57.8, 59.4, 61.3, 63.1, and 64.9 years. The schedule sensitivity of Model I was 64.2%, which was higher than that (57.5%) of the biennial periodic schedule. Model II included 11 screenings between the ages of 40 and 69 years and also showed a higher schedule sensitivity, especially for women aged 40 years as compared with the biennial screening. Conclusions This finding suggests that the threshold screening schedule for breast cancer increase the schedule sensitivity by reflecting the age-specific incidence rate of a population.

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“…Based on these numbers, women 50 to 69 years are expected to live until age 85. The majority would thus live beyond any realistic lead-time period (9,16).…”

Section: Methodsmentioning

confidence: 99%

Overdiagnosis in Mammographic Screening because of Competing Risk of Death

Falk

Hofvind

2016

Cancer Epidemiology, Biomarkers &Amp; Prevention

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Background: Different definitions and estimates of overdiagnosis in mammographic screening reflect a substantial need to investigate and understand the complexity of the issue. This modeling study aims to estimate the number of overdiagnosed women, defined as those diagnosed with breast cancer who die from any cause within the lead-time period.Methods: We used numbers from incidence and death statistics available online and published estimates of lead-time. Postulated cohorts of screened and not screened women ages 50 to 51 were followed for a period corresponding to 10 biennial screening exams during 20 years, and a further 10 years, to ages 78 to 79. The increase in breast cancer incidence because of screening was estimated based on lead-time. The proportion of women diagnosed with breast cancer who died within the lead-time period

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Estimating mean sojourn time and screening test sensitivity in breast cancer mammography screening: new results

Abstract: The new estimates indicate that screening detectable phase is longer than that found in previous mammography trials/programmes, but also that the sensitivity of the screening test is lower. Overall, the NBCSP detects more cancer cases than most previous trials/programmes.

Cited by 37 publications

References 21 publications

Estimation of natural history parameters of breast cancer based on non-randomized organized screening data: subsidiary analysis of effects of inter-screening interval, sensitivity, and attendance rate on reduction of advanced cancer

Estimation of natural history parameters of breast cancer based on non-randomized organized screening data: subsidiary analysis of effects of inter-screening interval, sensitivity, and attendance rate on reduction of advanced cancer

Scheduling mammography screening for the early detection of breast cancer in Korean women

Overdiagnosis in Mammographic Screening because of Competing Risk of Death

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