Shorter constitutional telomere length has been associated with increased cancer incidence. Furthermore, telomere shortening is observed in response to intensive chemotherapy and/or ionizing ...radiation exposure. We aimed to determine whether less telomere content was associated with treatment-related second malignant neoplasms (SMN) in childhood cancer survivors.
Using a nested case-control design, 147 cancer survivors with breast cancer, thyroid cancer, or sarcoma developing after treatment for childhood cancer (cases) were matched (1:1) with childhood cancer survivors without a SMN (controls). Cases and controls were matched by primary cancer diagnosis, years since diagnosis, age at the time of sample collection, years of follow-up from childhood cancer diagnosis, exposure to specific chemotherapy agents, and to specific radiation fields. We performed conditional logistic regression using telomere content as a continuous variable to estimate ORs with corresponding 95% confidence intervals (CI) for development of SMN. ORs were also estimated for specific SMN types, i.e., breast cancer, thyroid cancer, and sarcoma.
There was an inverse relationship between telomere content and SMN, with an adjusted OR of 0.3 per unit change in telomere length to single-copy gene ratio (95% CI, 0.09-1.02; P = 0.05). Patients with thyroid cancer SMN were less likely to have more telomere content (OR, 0.04; 95% CI, 0.00-0.55; P = 0.01), but statistically significant associations could not be demonstrated for breast cancer or sarcoma.
A relation between less telomere content and treatment-related thyroid cancer was observed, suggesting that shorter telomeres may contribute to certain SMNs in childhood cancer survivors.
Knowledge of family cancer history is important for assessing cancer risk and guiding screening recommendations.
To quantify how often throughout adulthood clinically significant changes occur in ...cancer family history that would result in recommendations for earlier or intense screening.
Descriptive study examining baseline and follow-up family history data from participants in the Cancer Genetics Network (CGN), a US national population-based cancer registry, between 1999 and 2009.
Adults with a personal history, family history, or both of cancer enrolled in the CGN through population-based cancer registries. Retrospective colorectal, breast, and prostate cancer screening-specific analyses included 9861, 2547, and 1817 participants, respectively; prospective analyses included 1533, 617, and 163 participants, respectively. Median follow-up was 8 years (range, 0-11 years). Screening-specific analyses excluded participants with the cancer of interest.
Percentage of individuals with clinically significant family histories and rate of change over 2 periods: (1) retrospectively, from birth until CGN enrollment and (2) prospectively, from enrollment to last follow-up.
Retrospective analysis revealed that the percentages of participants who met criteria for high-risk screening based on family history at ages 30 and 50 years, respectively, were as follows: for colorectal cancer, 2.1% (95% confidence interval CI, 1.8%-2.4%) and 7.1% (95% CI, 6.5%-7.6%); for breast cancer, 7.2% (95% CI, 6.1%-8.4%) and 11.4% (95% CI, 10.0%-12.8%); and for prostate cancer, 0.9% (95% CI, 0.5%-1.4%) and 2.0% (95% CI, 1.4%-2.7%). In prospective analysis, the numbers of participants who newly met criteria for high-risk screening based on family history per 100 persons followed up for 20 years were 2 (95% CI, 0-7) for colorectal cancer, 6 (95% CI, 2-13) for breast cancer, and 8 (95% CI, 3-16) for prostate cancer. The rate of change in cancer family history was similar for colorectal and breast cancer between the 2 analyses.
Clinically relevant family history of colorectal, breast, and prostate cancer that would result in recommendations for earlier or intense cancer screening increases between ages 30 and 50 years, although the absolute rate is low for prostate cancer.
Cancer survivors constitute 3.5% of the United States population, but second primary malignancies among this high-risk group now account for 16% of all cancer incidence. Although few data currently ...exist regarding the molecular mechanisms for second primary cancers and other late outcomes after cancer treatment, the careful measurement and documentation of potentially carcinogenic treatments (chemotherapy and radiotherapy) provide a unique platform for in vivo research on gene–environment interactions in human carcinogenesis. We review research priorities identified during a National Cancer Institute (NCI)–sponsored workshop entitled “Cancer Survivorship—Genetic Susceptibility and Second Primary Cancers.” These priorities include 1) development of a national research infrastructure for studies of cancer survivorship; 2) creation of a coordinated system for biospecimen collection; 3) development of new technology, bioinformatics, and biomarkers; 4) design of new epidemiologic methods; and 5) development of evidence-based clinical practice guidelines. Many of the infrastructure resources and design strategies that would facilitate research in this area also provide a foundation for the study of other important nonneoplastic late effects of treatment and psychosocial concerns among cancer survivors. These research areas warrant high priority to promote NCI's goal of eliminating pain and suffering related to cancer.
To characterize cancer risk in heterozygous p53 mutation carriers, we analyzed cancer incidence in 56 germline p53 mutation carriers and 3,201 noncarriers from 107 kindreds ascertained through ...patients with childhood soft-tissue sarcoma who were treated at the University of Texas M. D. Anderson Cancer Center. We systematically followed members in these kindreds for cancer incidence for >20 years and evaluated their p53 gene status. We found seven kindreds with germline p53 mutations that include both missense and truncation mutation types. Kaplan-Meier analysis showed similar cancer risks between 21 missense and 35 truncation p53 mutation carriers (log-rank χ2=0.04; P=.84). We found a significantly higher cancer risk in female carriers than in male carriers (log-rank χ2=12.1; P<.001), a difference not explained by an excess of sex-specific cancer. The calculated standardized incidence ratio (SIR) showed that mutation carriers had a risk for all types of cancer that was much higher than that for the general population (SIR = 41.1; 95% confidence interval CI 29.9–55.0) whereas noncarriers had a risk for all types of cancer that was similar to that in the general population (SIR = 0.9; 95% CI 0.8–1.0). The calculated SIRs showed a >100-fold higher risk of sarcoma, female breast cancer, and hematologic malignancies for the p53 mutation carriers and agreed with the findings of an earlier segregation analysis based on the same cohort. These results quantitatively illustrated the spectrum of cancer risk in germline p53 mutation carriers and will provide valuable reference for the evaluation and treatment of patients with cancer.
Early and late effects of cancer treatment are of increasing concern with growing survivor populations, but relevant data are sparse. We sought to determine the prevalence and hazard ratio of such ...effects in breast cancer cases. Women with invasive breast cancer and women with no cancer history recruited for a cancer research cohort completed a mailed questionnaire at a median of 10 years post-diagnosis or matched reference year (for the women without cancer). Reported medical conditions including lymphedema, osteopenia, osteoporosis, and heart disease (congestive heart failure, myocardial infarction, coronary heart disease) were assessed in relation to breast cancer therapy and time since diagnosis using Cox regression. The proportion of women currently receiving treatment for these conditions was calculated. Study participants included 2,535 women with breast cancer and 2,428 women without cancer (response rates 66.0 % and 50.4 %, respectively) Women with breast cancer had an increased risk of lymphedema (Hazard ratio (HR) 8.6; 95 % confidence interval (CI) 6.3–11.6), osteopenia (HR 2.1; 95 % CI 1.8–2.4), and osteoporosis (HR 1.5; 95 % CI 1.2–1.9) but not heart disease, compared to women without cancer Hazard ratios varied by treatment and time since diagnosis. Overall, 49.3 % of breast cancer cases reported at least one medical condition, and at 10 or more years post-diagnosis, 37.7 % were currently receiving condition-related treatment. Responses from survivors a decade following cancer diagnosis demonstrate substantial treatment-related morbidity, and emphasize the need for continued medical surveillance and follow-up care into the second decade post-diagnosis.
Carrier prediction models estimate the probability that a person has a BRCA mutation. We evaluated the accuracy of the BOADICEA model and compared its performance with that of other models (BRCAPRO, ...Myriad I and II, Couch, and Manchester Scoring System). We also studied the effect of extended family information on risk estimation using BOADICEA.
We compared the area under receiver operating characteristic curves generated from 472 families with one member tested for BRCA mutations. We calculated sensitivity, specificity, and predictive values at an estimated probability of 10% and explored the biases of carrier prediction.
BOADICEA performed better than the other models in Ashkenazi Jewish (AJ) families, BRCAPRO performed slightly better in non-AJ families, and Myriad II performed comparably well in both groups. Including extended family information in BOADICEA yielded slightly better performance than did limiting the information to second-degree relatives. Using a 10% cutoff point, BOADICEA and Myriad II were most sensitive in predicting BRCA1/2 mutations in AJ families, and Myriad II was most sensitive in non-AJ families. The Manchester Scoring System was the most sensitive and least specific in a subgroup of non-AJ families. BOADICEA and BRCAPRO tended to underestimate the observed risk at low estimated probabilities and overestimate it at higher probabilities.
The BOADICEA, BRCAPRO, and Myriad II models performed similarly. Including second-degree relatives slightly improved carrier prediction by BOADICEA. The Myriad II model was the easiest to implement.
Deleterious mutations of the BRCA1 and BRCA2 genes confer susceptibility to breast and ovarian cancer. At least 7 models for estimating the probabilities of having a mutation are used widely in ...clinical and scientific activities; however, the merits and limitations of these models are not fully understood.
To systematically quantify the accuracy of the following publicly available models to predict mutation carrier status: BRCAPRO, family history assessment tool, Finnish, Myriad, National Cancer Institute, University of Pennsylvania, and Yale University.
Cross-sectional validation study, using model predictions and BRCA1 or BRCA2 mutation status of patients different from those used to develop the models.
Multicenter study across Cancer Genetics Network participating centers.
3 population-based samples of participants in research studies and 8 samples from genetic counseling clinics.
Discrimination between individuals testing positive for a mutation in BRCA1 or BRCA2 from those testing negative, as measured by the c-statistic, and sensitivity and specificity of model predictions.
The 7 models differ in their predictions. The better-performing models have a c-statistic around 80%. BRCAPRO has the largest c-statistic overall and in all but 2 patient subgroups, although the margin over other models is narrow in many strata. Outside of high-risk populations, all models have high false-negative and false-positive rates across a range of probability thresholds used to refer for mutation testing.
Three recently published models were not included.
All models identify women who probably carry a deleterious mutation of BRCA1 or BRCA2 with adequate discrimination to support individualized genetic counseling, although discrimination varies across models and populations.
Numerous family studies have been performed to assess the associations between cancer incidence and genetic and non-genetic risk factors and to quantitatively evaluate the cancer risk attributable to ...these factors. However, mathematical models that account for a measured hereditary susceptibility gene have not been fully explored in family studies. In this report, we proposed statistical approaches to precisely model a measured susceptibility gene fitted to family data and simultaneously determine the combined effects of individual risk factors and their interactions. Our approaches are structured for age-specific risk models based on Cox proportional hazards regression methods. They are useful for analyses of families and extended pedigrees in which measured risk genotypes are segregated within the family and are robust even when the genotypes are available only in some members of a family. We exemplified these methods by analyzing six extended pedigrees ascertained through soft-tissue sarcoma patients with p53 germ-line mutations. Our analyses showed that germ-line p53 mutations and sex had significant interaction effects on cancer risk. Our proposed methods in family studies are accurate and robust for assessing age-specific cancer risk attributable to a measured hereditary susceptibility gene, providing valuable inferences for genetic counseling and clinical management.
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