Sojourn Time, Sensitivity and Positive Predictive Value of Mammography Screening for Breast Cancer in Women Aged 40–49

• Published in: International journal of epidemiology 1996-12, Vol.25 (6), p.1139-1145
• Main Authors: DUFFY, S W, CHEN, H H, TABAR, LASZLO, FAGERBERG, GUNNAR, PACI, EUGENIO
• Format: Article
• Language: English
• Subjects: Adult; Biological and medical sciences; breast cancer screening; Breast Neoplasms - diagnostic imaging; Breast Neoplasms - epidemiology; False Positive Reactions; Female; Gynecology. Andrology. Obstetrics; Humans; Incidence; Mammary gland diseases; Mammography - statistics & numerical data; Mass Screening - statistics & numerical data; Medical sciences; Middle Aged; positive predictive value; Predictive Value of Tests; sensitivity; Sensitivity and Specificity; sojourn time; Sweden - epidemiology; Time Factors; Tumors
• ISSN: 0300-5771; 1464-3685
• DOI: 10.1093/ije/25.6.1139

Duffy S W (MRC Biostatistics Unit, Institute of Public Health, University Forvie Site, Robinson Way, Cambridge CB2 2SR, UK), Chen H H, Tabar L, Fagerberg G and Paci E. Sojourn time, sensitivity and positive predictive value of mammography screening for breast cancer in women aged 40–49. International Journal of Epidemiology 1996; 25: 1139–1145. Background In mammographic screening for breast cancer in women aged 40–49, previous studies have found very low estimates of sensitivity and predictive value. Methods of estimation have, however, used primitive models with relatively strong assumptions and less than full use of the data. Methods Here we estimate the underlying preclinical incidence, mean sojoum time, sensitivity and positive predictive value by a variety of methods in a randomized trial of mammographic screening (The Swedish Two-County Trial) and a service screening programme (The Florence Programme, 1975–1986) in women aged 40–49 years. Results In the Two-County study, sensitivity estimates ranged from 72–83% and predictive value from 39–89%. In the Florence programme, sensitivity estimates ranged from 69–85% and predictive value was uniformly estimated as 100%. Conclusions The methods involving more explicit modelling of the disease process and fewer assumptions tended to find higher estimates of predictive value in the Two-County study. The results suggest that previously poor sensitivity and predictive value estimates may have been overpessimistic.