Diabetes and cancer are common diseases with tremendous impact on health worldwide. Epidemiologic evidence suggests that people with diabetes are at significantly higher risk for many forms of cancer. Type 2 diabetes and cancer share many risk factors, but potential biologic links between the two diseases are incompletely understood. Moreover, evidence from observational studies suggests that some medications used to treat hyperglycemia are associated with either increased or reduced risk of cancer. Against this backdrop, the American Diabetes Association and the American Cancer Society convened a consensus development conference in December 2009. Following a series of scientific presentations by experts in the field, the writing group independently developed this consensus report to address the following questions: 1. Is there a meaningful association between diabetes and cancer incidence or prognosis? 2. What risk factors are common to both diabetes and cancer? 3. What are possible biologic links between diabetes and cancer risk? 4. Do diabetes treatments influence risk of cancer or cancer prognosis? For each area, the authors were asked to address the current gaps in evidence and potential research and epidemiologic strategies for developing more definitive evidence in the future. Table 1 includes a summary of findings and recommendations. Recommendations in this report are solely the opinions of the authors and do not represent official position of the American Diabetes Association or the American Cancer Society. View this table: Table 1 Summary and recommendations ### 1. Is there a meaningful association between diabetes and cancer incidence or prognosis? Both diabetes and cancer are prevalent diseases whose incidence is increasing globally. Worldwide, the prevalence of cancer has been difficult to establish because many areas do not have cancer registries, but in 2008 there were an estimated 12.4 million new cancer cases diagnosed. The most commonly diagnosed cancers are lung/bronchus, breast, and colorectal, whereas the most common causes of cancer deaths are lung, stomach, and liver cancer (1). In the U.S., the most commonly diagnosed …

Epidemiologic evidence suggests that cancer incidence is associated with diabetes as well as certain diabetes risk factors and treatments. This consensus statement of experts assembled jointly by the American Diabetes Association and the American Cancer Society reviews the state of science concerning 1) the association between diabetes and cancer incidence or prognosis; 2) risk factors common to both diabetes and cancer; 3) possible biologic links between diabetes and cancer risk; and 4) whether diabetes treatments influence the risk of cancer or cancer prognosis. In addition, key unanswered questions for future research are posed.

The genetic and clinical heterogeneity of breast cancer makes the identification of effective therapies challenging. We designed I-SPY 2, a phase 2, multicenter, adaptively randomized trial to screen multiple experimental regimens in combination with standard neoadjuvant chemotherapy for breast cancer. The goal is to match experimental regimens with responding cancer subtypes. We report results for veliparib, a poly(ADP-ribose) polymerase (PARP) inhibitor, combined with carboplatin. In this ongoing trial, women are eligible for participation if they have stage II or III breast cancer with a tumor 2.5 cm or larger in diameter; cancers are categorized into eight biomarker subtypes on the basis of status with regard to human epidermal growth factor receptor 2 (HER2), hormone receptors, and a 70-gene assay. Patients undergo adaptive randomization within each biomarker subtype to receive regimens that have better performance than the standard therapy. Regimens are evaluated within 10 biomarker signatures (i.e., prospectively defined combinations of biomarker subtypes). Veliparib–carboplatin plus standard therapy was considered for HER2-negative tumors and was therefore evaluated in 3 signatures. The primary end point is pathological complete response. Tumor volume changes measured by magnetic resonance imaging during treatment are used to predict whether a patient will have a pathological complete response. Regimens move on from phase 2 if and when they have a high Bayesian predictive probability of success in a subsequent phase 3 neoadjuvant trial within the biomarker signature in which they performed well. With regard to triple-negative breast cancer, veliparib–carboplatin had an 88% predicted probability of success in a phase 3 trial. A total of 72 patients were randomly assigned to receive veliparib–carboplatin, and 44 patients were concurrently assigned to receive control therapy; at the completion of chemotherapy, the estimated rates of pathological complete response in the triple-negative population were 51% (95% Bayesian probability interval [PI], 36 to 66%) in the veliparib–carboplatin group versus 26% (95% PI, 9 to 43%) in the control group. The toxicity of veliparib–carboplatin was greater than that of the control. The process used in our trial showed that veliparib–carboplatin added to standard therapy resulted in higher rates of pathological complete response than standard therapy alone specifically in triple-negative breast cancer. (Funded by the QuantumLeap Healthcare Collaborative and others; I-SPY 2 TRIAL ClinicalTrials.gov number, NCT01042379.)

PURPOSE: To determine if changes in the concentration of choline-containing compounds (tCho) from before primary systemic therapy (PST) to within 24 hours after the first treatment enable prediction of clinical response in patients with locally advanced breast cancer. MATERIALS AND METHODS: Sixteen women with biopsy-confirmed locally advanced breast cancer scheduled to undergo doxorubicin-based PST were recruited. Magnetic resonance (MR) imaging and spectroscopy were performed at 4 T prior to treatment, within 24 hours after the first dose, and after the fourth dose. Lesion size was assessed by using gadolinium-enhanced MR imaging. Lesion tCho concentration was quantified by using single-voxel hydrogen 1 MR spectroscopy. Statistical analysis was performed by using the Pearson correlation coefficient and the Wilcoxon rank sum test. RESULTS: Fourteen of 16 patients completed the protocol. In one patient, the level of tCho was not measurable because of unfavorable lesion morphology for MR spectroscopy voxel ...

The heterogeneity of breast cancer makes identifying effective therapies challenging. The I-SPY 2 trial, a multicenter, adaptive phase 2 trial of neoadjuvant therapy for high-risk clinical stage II or III breast cancer, evaluated multiple new agents added to standard chemotherapy to assess the effects on rates of pathological complete response (i.e., absence of residual cancer in the breast or lymph nodes at the time of surgery). We used adaptive randomization to compare standard neoadjuvant chemotherapy plus the tyrosine kinase inhibitor neratinib with control. Eligible women were categorized according to eight biomarker subtypes on the basis of human epidermal growth factor receptor 2 (HER2) status, hormone-receptor status, and risk according to a 70-gene profile. Neratinib was evaluated against control with regard to 10 biomarker signatures (prospectively defined combinations of subtypes). The primary end point was pathological complete response. Volume changes on serial magnetic resonance imaging were used to assess the likelihood of such a response in each patient. Adaptive assignment to experimental groups within each disease subtype was based on Bayesian probabilities of the superiority of the treatment over control. Enrollment in the experimental group was stopped when the 85% Bayesian predictive probability of success in a confirmatory phase 3 trial of neoadjuvant therapy reached a prespecified threshold for any biomarker signature (“graduation”). Enrollment was stopped for futility if the probability fell to below 10% for every biomarker signature. Neratinib reached the prespecified efficacy threshold with regard to the HER2-positive, hormone-receptor–negative signature. Among patients with HER2-positive, hormone-receptor–negative cancer, the mean estimated rate of pathological complete response was 56% (95% Bayesian probability interval [PI], 37 to 73%) among 115 patients in the neratinib group, as compared with 33% among 78 controls (95% PI, 11 to 54%). The final predictive probability of success in phase 3 testing was 79%. Neratinib added to standard therapy was highly likely to result in higher rates of pathological complete response than standard chemotherapy with trastuzumab among patients with HER2-positive, hormone-receptor–negative breast cancer. (Funded by QuantumLeap Healthcare Collaborative and others; I-SPY 2 TRIAL ClinicalTrials.gov number, NCT01042379.)