Optimal Policies for Reducing Unnecessary Follow-Up Mammography Exams in Breast Cancer Diagnosis

References

• Alagoz O, Maillart LM, Schaefer AJ, Roberts MS (2004) The optimal timing of living-donor liver transplantation. Management Sci. 50(10):1420–1430.Link, Google Scholar
• Alagoz O, Maillart LM, Schaefer AJ, Roberts MS (2007) Determining the acceptance of cadaveric livers using an implicit model of the waiting list. Oper. Res. 55(1):24–36.Link, Google Scholar
• American Cancer Society (2011) Breast Cancer Facts and Figures: 2011–2012. American Cancer Society, Atlanta.Google Scholar
• American College of Radiology (1998) Breast Imaging Reporting And Data System (BI-RADS), 3rd ed. (American College of Radiology, Reston, VA).Google Scholar
• Anders CK, Hsu DS, Broadwater G, Acharya CR, Foekens JA, Zhang Y, Wang Y, Marcom PK, Marks JR, Febbo PG, et al. (2008) Young age at diagnosis correlates with worse prognosis and defines a subset of breast cancers with shared patterns of gene expression. J. Clinical Oncology 26(20):3324–3330.Crossref, Google Scholar
• Arias E (2006) United states life tables (2003) National Vital Statist. Rep. 54(14):1–40.Google Scholar
• Ayer T, Alagoz O, Chhatwal J, Shavlik J, Burnside ES, Kahn CE (2010) Breast cancer risk estimation with artificial neural networks revisited: Discrimination and calibration. Cancer 116(14):3310–3321.Crossref, Google Scholar
• Baker JA, Kornguth PJ, Lo JY, Williford ME, Floyd CE Jr (1995) Breast cancer: Prediction with artificial neural network based on BI-RADS standardized lexicon. Radiology 196(3):817–22.Crossref, Google Scholar
• Barlow RE, Proschan F (1965) Mathematical Theory of Reliability (Wiley, New York).Google Scholar
• Barlow WE, Chi C, Carney PA, Taplin SH, D'Orsi C, Cutter G, Hendrick RE, Elmore JG (2004) Accuracy of screening mammography interpretation by characteristics of radiologists. JNCI 96(24):1840–1850.Crossref, Google Scholar
• Barton MB, Morley DS, Moore S, Allen JD, Kleinman KP, Emmons KM, Fletcher SW (2004) Decreasing women's anxieties after abnormal mammograms: A controlled trial. JNCI 96(7):529–538.Crossref, Google Scholar
• Bassett LW, Hendrick RE, Bassford TL, et al. (1994) Quality determinants of mammography: Clinical practice guideline 13. Agency for Health Care Policy and Research, Public Health Service, U.S. Department of Health and Human Services, Rockville, MD.Google Scholar
• Baum JK, Hanna LG, Acharyya S, Mahoney MC, Conant EF, Bassett LW, Pisano ED (2011) Use of BI-RADS 3–probably benign category in the American College of Radiology imaging network digital mammographic imaging screening trial. Radiology 260(1):61–67.Crossref, Google Scholar
• Beam CA, Layde PM, Sullivan DC (1996) Variability in the interpretation of screening mammograms by us radiologists. Findings from a national sample. Arch. Internal Medicine 156(2):209–213.Crossref, Google Scholar
• Berg WA, Campassi C, Langenberg P, Sexton MJ (2000) Breast imaging reporting and data system: Inter-and intraobserver variability in feature analysis and final assessment. Amer. J. Roentgenology 174(6):1769–1777.Crossref, Google Scholar
• Berry DA, Cronin KA, Plevritis SK, Fryback DG, Clarke L, Zelen M, Mandelblatt JS, Yakovlev AY, Habbema JDF, Feuer EJ (2005) Effect of screening and adjuvant therapy on mortality from breast cancer. NEJM 353(17):1784–1792.Crossref, Google Scholar
• Brodersen J, Siersma VD (2013) Long-term psychosocial consequences of false-positive screening mammography. Ann. Family Medicine 11(2):106–115.Crossref, Google Scholar
• Burnside ES, Chhatwal J, Alagoz O (2012) What is the optimal threshold at which to recommend breast biopsy? PloS ONE 7(11):e48820.Crossref, Google Scholar
• Burnside ES, Rubin DL, Fine JP, Shachter RD, Sisney GA, Leung WK (2006) Bayesian network to predict breast cancer risk of mammographic microcalcifications and reduce number of benign biopsy results: Initial experience. Radiology 240(3):666–673.Crossref, Google Scholar
• Burnside ES, Davis J, Chhatwal J, Alagoz O, Lindstrom MJ, Geller BM, Littenberg B, Shaffer KA, Kahn CE, Page CD (2009) Probabilistic computer model developed from clinical data in national mammography database format to classify mammographic findings. Radiology 251(3):663–672.Crossref, Google Scholar
• Chhatwal J (2008) Optimal management of mammography findings for breast cancer diagnosis: Patient's perspective. Ph.D. dissertation, University of Wisconsin-Madison, Madison.Google Scholar
• Chhatwal J, Alagoz O, Burnside ES (2010) Optimal breast biopsy decision-making based on mammographic features and demographic factors. Oper. Res. 58(6):1577–1591.Link, Google Scholar
• Chhatwal J, Alagoz O, Lindstrom MJ, Kahn CE, Shaffer KA, Burnside ES (2009) A logistic regression model to aid breast cancer diagnosis based on the national mammography database format. Amer. J. Roentgenology 192(4):1117–1127.Crossref, Google Scholar
• Cyrlak D (1988) Induced costs of low-cost screening mammography. Radiology 168(3):661–663.Crossref, Google Scholar
• Drummond MF (2005) Methods for the Economic Evaluation of Health Care Programmes (Oxford University Press, Oxford, UK).Google Scholar
• Gail MH, Brinton LA, Byar DP, Corle DK, Green SB, Schairer C, Mulvihill JJ (1989) Projecting individualized probabilities of developing breast cancer for white females who are being examined annually. JNCI 81(24):1879–1886.Crossref, Google Scholar
• Geller BM, Barlow WE, Ballard-Barbash R, Ernster VL, Yankaskas BC, Sickles EA, Carney PA, Dignan MB, Rosenberg RD, Urban N, Zheng Y, Taplin SH (2002) Use of the American College of Radiology BI-RADS to report on the mammographic evaluation of women with signs and symptoms of breast disease. Radiology 222(2):536–542.Crossref, Google Scholar
• Hall FM, Storella JM, Silverstone DZ, Wyshak G (1988) Nonpalpable breast lesions: Recommendations for biopsy based on suspicion of carcinoma at mammography. Radiology 167(2):353–358.Crossref, Google Scholar
• Haybittle JL (1998) Life expectancy as a measurement of the benefit shown by clinical trials of treatment for early breast cancer. Clinical Oncology 10(2):92–94.Crossref, Google Scholar
• Iravani SMR, Duenyas I (2002) Integrated maintenance and production control of a deteriorating production system. IIE Trans. 34(5):423–435.Crossref, Google Scholar
• Jemal A, Siegel R, Ward E, Murray T, Xu J, Thun MJ (2007) Cancer statistics, 2007. CA: A Cancer J. Clinicians 57(1):43–66.Crossref, Google Scholar
• Jesneck JL, Nolte LW, Baker JA, Floyd CE, Lo JY (2006) Optimized approach to decision fusion of heterogeneous data for breast cancer diagnosis. Medical Phys. 33(8):2945–2954.Crossref, Google Scholar
• Jiang Y, Metz CE (2010) BI-RADS data should not be used to estimate ROC curves. Radiology 256(1):29–31.Crossref, Google Scholar
• Jiang Y, Nishikawa RM, Schmidt RA, Toledano AY, Doi K (2001) Potential of computer-aided diagnosis to reduce variability in radiologists' interpretations of mammograms depicting microcalcifications. Radiology 220(3):787–794.Crossref, Google Scholar
• Kerlikowske K, Smith-Bindman R, Sickles EA (2003) Short-interval follow-up mammography: Are we doing the right thing? JNCI 95(6):418–419.Crossref, Google Scholar
• Kerlikowske K, Grady D, Barclay J, Frankel SD, Ominsky SH, Sickles EA, Ernster V (1998) Variability and accuracy in mammographic interpretation using the American College of Radiology breast imaging reporting and data system. JNCI 90(23):1801–1809.Crossref, Google Scholar
• Kolata G (2009) Panel urges mammograms at 50, not 40. New York Times (November 16). Google Scholar
• Kopans DB (1992) The positive predictive value of mammography. Amer. J. Roentgenology 158(3):521–526.Crossref, Google Scholar
• Monticciolo DL, Caplan LS (2004) The American College of Radiology's BI-RADS 3 classification in a nationwide screening program: Current assessment and comparison with earlier use. Breast J. 10(2):106–110.Crossref, Google Scholar
• National Center for Health Statistics (2007) Health, United States, 2006 with Chartbook on Trends in the Health of Americans (National Center for Health Statistics, Hyattsville, MD).Google Scholar
• Ong G, Austoker J, Brett J (1997) Breast screening: Adverse psychological consequences one month after placing women on early recall because of a diagnostic uncertainty. A multicentre study. J. Medical Screening 4(3):158–168.Crossref, Google Scholar
• Orel SG, Kay N, Reynolds C, Sullivan DC (1999) BI-RADS categorization as a predictor of malignancy. Radiology 211(3):845–850.Crossref, Google Scholar
• Pliskin JS, Shepard DS, Weinstein MC (1980) Utility functions for life years and health status. Oper. Res. 28(1):206–224.Link, Google Scholar
• Puterman ML (1994) Markov Decision Processes: Discrete Stochastic Dynamic Programming (John Wiley & Sons, New York).Crossref, Google Scholar
• Qaseem A, Snow V, Sherif K, Aronson M, Weiss KB, Owens DK, Clinical Efficacy Assessment Subcommittee of the American College of Physicians (2007) Screening mammography for women 40 to 49 years of age: A clinical practice guideline from the American college of physicians. Ann. Internal Medicine 146(7):511–515.Crossref, Google Scholar
• Rubin E (1999a) Commentary on Dr. Sickles's viewpoint. Radiology 213(1):21.Crossref, Google Scholar
• Rubin E (1999b) Six-month follow-up: An alternative view. Radiology 213(1):15–18.Crossref, Google Scholar
• Sandıkçı B, Maillart LM, Schaefer AJ, Alagoz O, Roberts MS (2008) Estimating the patients price of privacy in liver transplantation. Oper. Res. 56(6):1393–1410.Link, Google Scholar
• Shechter SM, Bailey MD, Schaefer AJ, Roberts MS (2008) The optimal time to initiate HIV therapy under ordered health states. Oper. Res. 56(1):20–33.Link, Google Scholar
• Sickles EA (1991) Periodic mammographic follow-up of probably benign lesions: Results in 3,184 consecutive cases. Radiology 179(2):463–468.Crossref, Google Scholar
• Sickles EA (1999a) Commentary on Dr. Rubin's viewpoint. Radiology 213(1):19–20.Crossref, Google Scholar
• Sickles EA (1999b) Probably benign breast lesions: When should follow-up be recommended and what is the optimal follow-up protocol? Radiology 213(1):11–14.Crossref, Google Scholar
• Sickles EA, Miglioretti DL, Ballard-Barbash R, Geller BM, Leung JWT, Rosenberg RD, Smith-Bindman R, Yankaskas BC (2005) Performance benchmarks for diagnostic mammography. Radiology 235(3):775–790.Crossref, Google Scholar
• U.S. Preventative Service Task Forces (2009) Screening for breast cancer: Recommendations and rationale. Ann. Internal Medicine 151(10):716–726.Crossref, Google Scholar
• Varas X, Leborgne F, Leborgne JH (1992) Nonpalpable, probably benign lesions: Role of follow-up mammography. Radiology 184(2):409–414.Crossref, Google Scholar
• Varas X, Leborgne JH, Leborgne F, Mezzera J, Jaumandreu S, Leborgne F (2002) Revisiting the mammographic follow-up of BI-RADS category 3 lesions. Amer. J. Roentgenology 179(3):691–695.Crossref, Google Scholar
• Velanovich V (1995) Immediate biopsy versus observation for abnormal findings on mammograms: An analysis of potential outcomes and costs. Amer. J. Surgery 170(4):327–332.Crossref, Google Scholar
• Vizcaíno I, Gadea L, Andreo L, Salas D, Ruiz-Perales F, Cuevas D, Herranz C, Bueno F (2001) Short-term follow-up results in 795 nonpalpable probably benign lesions detected at screening mammography. Radiology 219(2):475–483.Crossref, Google Scholar
• Wright JC, Weinstein MC (1998) Gains in life expectancy from medical interventions standardizing data on outcomes. New England J. Medicine 339(6):380–386.Crossref, Google Scholar
• Yasmeen S, Romano PS, Pettinger M, Chlebowski RT, Robbins JA, Lane DS, Hendrix SL (2003) Frequency and predictive value of a mammographic recommendation for short-interval follow-up. JNCI 95(6):429–436.Crossref, Google Scholar