© 2001 by Oxford University Press
Journal of the National Cancer Institute, Vol. 93, No. 5, 333,
March 7, 2001
© 2001 Oxford University Press
IN THIS ISSUE |
Women and their clinicians are encouraged to use risk estimates derived from statistical models, primarily the model of Gail et al., to aid decision making regarding potential prevention options for breast cancer, including chemoprevention with tamoxifen. Rockhill et al. (p. 358) used women in the Nurses’ Health Study to evaluate the Gail et al. model 2, which predicts the risk of developing invasive breast cancer. They looked at two statistical concepts—goodness of fit and discriminatory accuracy at the individual level. They concluded that the model fit well in the total sample in terms of predicting numbers of breast cancer cases in specific risk factor strata, but it had modest discriminatory accuracy at the individual level. This finding has implications for use of the model in clinical counseling of individual women.
In an editorial, Gail and Costantino (p. 334) commend Rockhill et al. for challenging researchers to develop breast cancer risk projection models with greater discriminatory accuracy. They comment, however, that it is likely that a simple model based on data easily acquired from the medical history, such as the model of Gail et al., will remain useful for identifying women who could benefit from preventive interventions or who require more discriminating but more invasive or costly tests to predict risk.
Genetic Variability in Human T-Cell Leukemia Virus Type 1
Human T-cell leukemia virus type 1 (HTLV-1), the causative agent of adult T-cell leukemia/lymphoma (ATLL), shows intrapatient genetic variability. Although HTLV-1 can replicate via the reverse transcription (RT) of virion RNA to a double-stranded DNA provirus, its replication occurs predominantly via clonal expansion of infected cells. Mortreux et al. (p. 367) designed a strategy to distinguish somatic mutations from RT-associated substitutions. They isolated and sequenced several HTLV-1 provirus 3' segments together with flanking cellular sequences. For 60% of the infected cell clones, 8%–80% of cells harbored a mutated HTLV-1 provirus without evidence of RT-associated mutations. Some infected clones carried multiple discrete substitutions or deletions, indicating progressive accumulation of mutations during clonal expansion. Furthermore, substitutions in flanking cellular sequences suggested postintegration occurrence of somatic mutations. The investigators conclude that accumulation of such mutations, presumably coupled with clonal selection, can result in transformed cellular phenotypes seen in ATLL.
In an editorial, Mansky (p. 336) points out the paucity of information regarding why HTLV-1 and related viruses have chosen a different and unusual lifestyle compared with that of other retroviruses. He suggests the need for more studies to unravel the association of HTLV-1 replication as a provirus, the host immune response, and low risk of developing ATLL in HTLV-1-infected individuals.
"These findings suggest that somatic mutations after integration, presumably coupled with selection, help move the cellular clones toward a transformed phenotype, of which ATLL is the end point."
—Mortreux et al.
Environmental Tobacco Smoke Carcinogens in Nonsmokers
Environmental tobacco smoke (ETS) is associated with lung cancer in nonsmokers. Anderson et al. (p. 378) measured metabolites of tobacco carcinogens in 23 women whose partners smoked and in 22 women whose partners did not smoke. They found that levels of the tobacco metabolites were statistically significantly higher in women exposed to ETS than in women who were not exposed to ETS. Thus, women exposed to ETS take up and metabolize tobacco carcinogens, which, they conclude, could increase their risk of lung cancer.
Antiangiogenic Therapy and Tumor Growth
Angiogenesis, the generation of new blood vessels, is critical for cancer growth and progression. It is not known whether antiangiogenic therapies are effective in vivo against cancers that differ in their rate of growth or degree of vascularity. However, it has been assumed that, because cytotoxic chemotherapy is more effective against rapidly growing cancers than against slowly growing ones, antiangiogenic therapy will be effective in a similar way. Beecken et al. (p. 382) compared the effectiveness of two antiangiogenic therapies, TNP-470 and angiostatin, against both a rapidly growing, highly vascularized human bladder cancer and a slowly growing, poorly vascularized human bladder cancer grown in mice. The authors found that the angiogenesis inhibitors were equally effective against both the rapidly growing and the slowly growing cancers, independent of the degree of vascularity. They conclude that, even though most human cancers grow slowly, angiogenesis inhibitors may prove to be an effective addition to cancer therapy options.
Prostate Cancer and Ethnicity
African-Americans have the highest incidence of prostate cancer and twice the risk of non-Hispanic whites for presenting with advanced-stage disease. Explanations to account for the disparity among ethnic groups include demographic or socioeconomic characteristics and differences in tumor biology that are attributable to dietary, hormonal, or molecular factors. Using data from a population-based cohort of men with newly diagnosed prostate cancer (the Prostate Cancer Outcomes Study), Hoffman et al. (p. 388) assessed the association between race/ethnicity and prostate cancer clinical stage after adjusting for demographic, socioeconomic, clinical, and pathologic factors. The authors found that these factors accounted for the increased relative risk in advanced-stage prostate cancer in Hispanic men but not in African-American men. The authors conclude that any efforts to reduce prostate cancer mortality in African-American men will have to consider racial or ethnic disparity in clinical stage at diagnosis.
"Ultimately, any efforts to reduce prostate cancer mortality in African-Americans will have to address the factors accounting for the racial disparity in clinical stage at diagnosis."
—Hoffman et al.
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