Validation of the Gail et al. Model of Breast Cancer Risk Prediction and Implications for Chemoprevention

Rockhill, Beverly; Spiegelman, Donna; Byrne, Celia; Hunter, David J.; Colditz, Graham A.

doi:10.1093/jnci/93.5.358

Cited by 544 publications

(357 citation statements)

References 17 publications

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“…Furthermore, the discriminatory power of the current nomogram is within the range of other tools commonly used for routine counseling and decision-making in clinical oncology. 28,29 Refinement of the nomogram, with the identification of additional clinical, pathologic, laboratory, and molecular predictors may, nonetheless, optimize the value of this tool.…”

Section: Discussionmentioning

confidence: 99%

Nomogram for predicting survival in patients with unresectable and/or metastatic urothelial cancer who are treated with cisplatin‐based chemotherapy

Galsky

Moshier

Krege³

et al. 2013

Cancer

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BACKGROUND:The current study was conducted to develop a pretreatment prognostic model for patients with unresectable and/or metastatic urothelial cancer who were treated with first-line, cisplatin-based chemotherapy. METHODS: Individual data were pooled from 399 patients who were enrolled on 8 phase 2 and 3 trials evaluating cisplatin-based, first-line chemotherapy in patients with metastatic urothelial carcinoma. Variables selected for inclusion in the model were combined in a Cox proportional hazards model to produce a points-based nomogram with which to predict the median, 1-year, 2-year, and 5-year survival. The nomogram was validated externally using data from a randomized trial of the combination of methotrexate, vinblastine, doxorubicin plus cisplatin versus docetaxel plus cisplatin. RESULTS: The median survival of the development cohort was 13.8 months (95% confidence interval, 12.1 months-16.0 months); 68.2% of the patients had died at the time of last follow-up. On multivariable analysis, the number of visceral metastatic sites, Eastern Cooperative Oncology Group performance status, and leukocyte count were each found to be associated with overall survival (P <.05), whereas the site of the primary tumor and the presence of lymph node metastases were not. All 5 variables were included in the nomogram. When subjected to internal validation, the nomogram achieved a bootstrap-corrected concordance index of 0.626. When applied to the external validation cohort, the nomogram achieved a concordance index of 0.634. Calibration plots suggested that the nomogram was well calibrated for all predictions. CONCLUSIONS: Based on routinely measured pretreatment variables, a nomogram was constructed that predicts survival in patients with unresectable and/or metastatic urothelial cancer who are treated with cisplatin-based chemotherapy. This model may be useful in patient counseling and clinical trial design. Cancer 2013;119:3012-9. V C 2013 American Cancer Society.KEYWORDS: urothelial cancer; bladder cancer; prognosis; metastatic; chemotherapy; cisplatin. INTRODUCTIONContemporary cisplatin-based combination chemotherapy regimens achieve objective responses in approximately 50&percnt to 60% of patients with metastatic urothelial cancer.1,2 Although response durations are generally short, and the median overall survival of patients with unresectable and/or metastatic urothelial cancer is only approximately 14 months, significant heterogeneity exists with regard to patient outcomes.2 Long-term follow-up of clinical trials has demonstrated that approximately 10% to 20% of patients are alive at 5 years.1,3 The ability to predict individual patient outcomes has clear implications with regard to both patient counseling and patient stratification on clinical trials.Prognostic models have previously been developed for chemotherapy-naive patients with unresectable and/or metastatic urothelial cancer. In 1998, Bajorin et al identified Karnofsky performance status and the presence of visceral metastases as independent predictors ...

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Section: Discussionmentioning

confidence: 99%

Nomogram for predicting survival in patients with unresectable and/or metastatic urothelial cancer who are treated with cisplatin‐based chemotherapy

Galsky

Moshier

Krege³

et al. 2013

Cancer

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“…20,47 Until we have a better knowledge of how these factors relate to risk interpretation, and because the women's backgrounds and experiences vary widely, it might be valuable to spend time assessing each woman's preferred risk presentation before adopting a specific strategy. If this is not feasible in clinical settings, it may prove valuable to use a combination of approaches to communicate individual risk rather than using only crude age-probabilities, which is the format used in most online self-risk assessment models 9,10,[48][49][50] Given the increasing use of, and accessibility to, risk prediction models, our findings highlight the relevance of considering the preferences of both the woman to whom the risk is communicated and the professional.…”

Section: Discussionmentioning

confidence: 99%

A focus group study on breast cancer risk presentation: one format does not fit all

et al. 2012

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Identifying a strategy that would optimize both the communication and understanding of the individual breast cancer risk remains a considerable challenge. This study explored the preferences of women with a family history of breast cancer about six presentation formats of individual breast cancer risk, as calculated from a risk prediction model. Thirty-four unaffected women attending genetic counseling because of a family history of breast cancer participated in six focus groups conducted in Qué bec City (2), Montré al (2) and Toronto (2), Canada. Six risk formats were presented for a fictitious case involving a 35-year-old woman (1-numerical: cumulative risk probabilities by age until 80 years; 2-risk curves: probabilities expressed in a risk curve that also provided a risk curve for a woman with no family history in first-degree relatives; 3-relative risk of breast cancer by age 80 years; 4 and 5-absolute risk of breast cancer and absolute chance of not developing breast cancer in the next 20 years; 6-qualitative: color-coded figure). Participants were asked to indicate their appreciation of each format. A group discussion followed during which participants commented on each format. The most and least appreciated formats were risk curves and relative risk, respectively. Overall, participants advocated the use of formats that combine quantitative, qualitative and visual features. Using a combination of approaches to communicate individual breast cancer risks could be associated with higher satisfaction of counselees. Given the increasing use of risk prediction models, it may be relevant to consider the preferences of both the counselee and the professional.

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“…the agreement between expected (E) and observed (O) rates, was assessed overall and within pre-specified groups of participants. The 95% CIs for the expected:observed ratio were estimated by assuming Poisson variance [18]. The overall bias in expected event rates was estimated as 100(E−O)/O [19].…”

Section: Cardiovascular Risk Modelsmentioning

confidence: 99%

The Framingham and UK Prospective Diabetes Study (UKPDS) risk equations do not reliably estimate the probability of cardiovascular events in a large ethnically diverse sample of patients with diabetes: the Action in Diabetes and Vascular Disease: Preterax and Diamicron-MR Controlled Evaluation (ADVANCE) Study

et al. 2010

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Aims/hypothesis Available multivariable equations for cardiovascular risk assessment in people with diabetes have been derived either from the general population or from populations with diabetes. Their utility and comparative performance in a contemporary group of patients with type 2 diabetes are not well established. Diabetologia (2010) 53:821-831 DOI 10.1007/s00125-010-1681 Framingham and the UKPDS risk equations in 7,502 individuals with type 2 diabetes without prior known CVD at their enrolment in the trial. Results The risk of major CVD was overestimated by 170% (95% CI 146-195%) and 202% (176-231%) using the two Framingham equations. The risk of major coronary heart disease was overestimated by 198% (162-238%) with the UKPDS, and by 146% (117-179%) and 289% (243-341%) with the two different Framingham equations, respectively. The risks of stroke events were also overestimated with the UKPDS and one of the Framingham equations. The ability of these equations to rank risk among ADVANCE participants was modest, with c-statistics ranging from 0.57 to 0.71. Results stratified by sex, treatment allocation and ethnicity were broadly similar. Conclusions/interpretation Application of the Framingham and UKPDS risk equations to a contemporary treated group of patients with established type 2 diabetes is likely to substantially overestimate cardiovascular risk.

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Validation of the Gail et al. Model of Breast Cancer Risk Prediction and Implications for Chemoprevention

Cited by 544 publications

References 17 publications

Nomogram for predicting survival in patients with unresectable and/or metastatic urothelial cancer who are treated with cisplatin‐based chemotherapy

Nomogram for predicting survival in patients with unresectable and/or metastatic urothelial cancer who are treated with cisplatin‐based chemotherapy

A focus group study on breast cancer risk presentation: one format does not fit all

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