Margaret T. Mandelson

BACKGROUND: Screening mammography is the best method to reduce mortality from breast cancer, yet some breast cancers cannot be detected by mammography. Cancers diagnosed after a negative mammogram are known as interval cancers. This study investigated whether mammographic breast density is related to the risk of interval cancer. METHODS: Subjects were selected from women participating in mammographic screening from 1988 through 1993 in a large health maintenance organization based in Seattle, WA. Women were eligible for the study if they had been diagnosed with a first primary invasive breast cancer within 24 months of a screening mammogram and before a subsequent one. Interval cancer case subjects (n = 149) were women whose breast cancer occurred after a negative or benign mammographic assessment. Screen-detected control subjects (n = 388) were diagnosed after a positive screening mammogram. One radiologist, who was blinded to cancer status, assessed breast density by use of the American College of Radiology Breast Imaging Reporting and Data System. RESULTS: Mammographic sensitivity (i.e., the ability of mammography to detect a cancer) was 80% among women with predominantly fatty breasts but just 30% in women with extremely dense breasts. The odds ratio (OR) for interval cancer among women with extremely dense breasts was 6.14 (95% confidence interval [CI] = 1.95-19.4), compared with women with extremely fatty breasts, after adjustment for age at index mammogram, menopausal status, use of hormone replacement therapy, and body mass index. When only those interval cancer cases confirmed by retrospective review of index mammograms were considered, the OR increased to 9.47 (95% CI = 2.78-32.3). CONCLUSION: Mammographic breast density appears to be a major risk factor for interval cancer.

PURPOSE: This study was conducted to evaluate the effect of stage at diagnosis, age, and level of comorbidity (presence of other illness) on the costs of treating three types of cancer among members of a health maintenance organization. METHODS: Among 388,000 members enrolled anytime during 1990 and 1991 in Group Health Cooperative (GHC) of Puget Sound (Washington State), we estimated the total and net direct costs of medical care for colon, prostate, and breast cancers, including both incident (290, 554, and 645 patients, respectively) and prevalent (1046, 1295, and 2299 patients, respectively) cases. We summarized costs for initial, continuing, and terminal phases of care. Net costs were the difference between the costs of the care of each case subject and the average costs of the care for all enrollees without the cancer of interest who were of the same sex and in the same 5-year age group. Differences in estimated total and net costs by stage at diagnosis, age, and comorbidity were separately evaluated using multivariate regression modeling. All P values were two-sided. Comorbidity was based on a score calculated from 1988 pharmacy data. RESULTS: Total costs of initial care increased with stage at diagnosis for colon (P = .0013) and breast (P < .0001) cancer cases, but not for prostate cancer cases. Total initial costs decreased with age for prostate (P = .0225) and breast (P = .0002) cancers but did not change with degree of comorbidity for any of the three cancers. Total continuing medical care costs increased with stage at diagnosis for colon (P < .0001) and breast (P < .0001) cancer cases but not for prostate cancer cases. Total terminal care costs were similar by stage for all three cancers. Net initial costs differed with stage for all three cancers (P < .05). Net continuing care costs increased with stage (P < .0001) and decreased with age (P < .001) for colon and breast cancers but not for prostate cancer. Net continuing care costs decreased with comorbidity for all three cancers (P = .004, P = .011, and P < .0001 for colon, prostate, and breast cancers, respectively). Among regional stage cancers, continuing care costs decreased with age for colon (P < .0017) and breast (P = .033) cancers but not for prostate cancers. CONCLUSIONS: The results show that total costs vary by stage at diagnosis and age, but the patterns of variation differ for each cancer. Costs of cancer are not simply additive to costs of other conditions. IMPLICATIONS: More needs to be done to explore the reasons and implications of age-related cost differences. Cost-effectiveness analyses of cancer control interventions that shift cancer stage distributions may need to consider both the age and comorbidity of the target populations.

Journal Article Cigarette Smoking and the Risk of Anogenital Cancer Get access Janet R. Daling, Janet R. Daling 1Division of Public Health Sciences, Fred Hutchinson Cancer Research CenterSeattle, WA.2Department of Epidemiology, University of WashingtonSeattle, WA. Reprint requests to Dr. Janet R. Daling, Fred Hutchinson Cancer Research Center, 1124 Columbia Street (MP 381), Seattle, WA 98104. Search for other works by this author on: Oxford Academic PubMed Google Scholar Karen J. Sherman, Karen J. Sherman 1Division of Public Health Sciences, Fred Hutchinson Cancer Research CenterSeattle, WA.2Department of Epidemiology, University of WashingtonSeattle, WA. Search for other works by this author on: Oxford Academic PubMed Google Scholar T. Gregory Hislop, T. Gregory Hislop 3British Columbia Cancer AgencyVancouver, British Columbia, Canada. Search for other works by this author on: Oxford Academic PubMed Google Scholar Christopher Maden, Christopher Maden 1Division of Public Health Sciences, Fred Hutchinson Cancer Research CenterSeattle, WA.2Department of Epidemiology, University of WashingtonSeattle, WA. Search for other works by this author on: Oxford Academic PubMed Google Scholar Margaret T. Mandelson, Margaret T. Mandelson 1Division of Public Health Sciences, Fred Hutchinson Cancer Research CenterSeattle, WA.2Department of Epidemiology, University of WashingtonSeattle, WA. Search for other works by this author on: Oxford Academic PubMed Google Scholar Anna Marie Beckmann, Anna Marie Beckmann 1Division of Public Health Sciences, Fred Hutchinson Cancer Research CenterSeattle, WA. Search for other works by this author on: Oxford Academic PubMed Google Scholar Noel S. Weiss Noel S. Weiss 1Division of Public Health Sciences, Fred Hutchinson Cancer Research CenterSeattle, WA.2Department of Epidemiology, University of WashingtonSeattle, WA. Search for other works by this author on: Oxford Academic PubMed Google Scholar American Journal of Epidemiology, Volume 135, Issue 2, 15 January 1992, Pages 180–189, https://doi.org/10.1093/oxfordjournals.aje.a116270 Published: 15 January 1992 Article history Received: 18 July 1991 Revision received: 10 October 1991 Published: 15 January 1992