A Cost-Effectiveness Evaluation of Germline BRCA1 and BRCA2 Testing in UK Women with Ovarian Cancer

Objectives

To evaluate the long-term cost-effectiveness of germline BRCA1 and BRCA2 (collectively termed “BRCA”) testing in women with epithelial ovarian cancer, and testing for the relevant mutation in first- and second-degree relatives of BRCA mutation–positive individuals, compared with no testing. Female BRCA mutation–positive relatives of patients with ovarian cancer could undergo risk-reducing mastectomy and/or bilateral salpingo-oophorectomy.

Multiple diseases in carrier probability estimation: accounting for surviving all cancers other than breast and ovary in BRCAPRO

Mendelian models can predict who carries an inherited deleterious mutation of known disease genes based on family history. For example, the BRCAPRO model is commonly used to identify families who carry mutations of BRCA1 and BRCA2, based on familial breast and ovarian cancers. These models incorporate the age of diagnosis of diseases in relatives and current age or age of death. We develop a rigorous foundation for handling multiple diseases with censoring. We prove that any disease unrelated to mutations can be excluded from the model, unless it is sufficiently common and dependent on a mutation-related disease time. Furthermore, if a family member has a disease with higher probability density among mutation carriers, but the model does not account for it, then the carrier probability is deflated. However, even if a family only has diseases the model accounts for, if the model excludes a mutation-related disease, then the carrier probability will be inflated. In light of these results, we extend BRCAPRO to account for surviving all non-breast/ovary cancers as a single outcome. The extension also enables BRCAPRO to extract more useful information from male relatives. Using 1500 families from the Cancer Genetics Network, accounting for surviving other cancers improves BRCAPRO's concordance index from 0.758 to 0.762 (p=0.046), improves its positive predictive value from 35 to 39 per cent (p<10(-6)) without impacting its negative predictive value, and improves its overall calibration, although calibration slightly worsens for those with carrier probability <10 per cent. Copyright (c) 2008 John Wiley & Sons, Ltd.     

Association of parity and ovarian cancer risk by family history of breast or ovarian cancer in a population-based study of postmenopausal women.

Although parity is associated with a decreased risk of ovarian cancer in the general population, this association among women with a family history is less clear. We examined this question in a prospective cohort of 31,377 Iowa women 55-69 years of age at baseline. Relative risks (RRs) and 95% confidence intervals (CIs) were estimated through Cox regression. We identified 181 incident epithelial ovarian cancers through 13 years of follow-up. At baseline, 14% of the women reported breast or ovarian cancer in a first-degree relative, and an additional 12% reported a family history in a second-degree relative. Among women without a family history of breast or ovarian cancer in a first-degree relative, nulliparous women were at slightly increased risk of ovarian cancer (RR = 1.4, 95% CI = 0.9-2.4) compared with parous women, whereas among women with a family history, nulliparous women were at a much higher risk (RR = 2.7, 95% CI = 1.1-6.6) than parous women. Similar results were seen when family history included first- or second-degree relatives with breast or ovarian cancer or a first- or second-degree relative with ovarian cancer only. Nulliparity may be more strongly associated with an increased risk of ovarian cancer among women with a family history of breast or ovarian cancer, compared with women who do not have a family history of those cancers.     

Estimating the age-at-onset function using life-table methods

In the analysis of dominantly inherited diseases, the age-at-onset function is often estimated from the observed age-at-onset distribution of cases. This estimate is confounded with the age distribution of the population from which the cases were sampled and is accurate only if there are no competing causes of death. In this paper, we present a straightforward method for calculating a more accurate age-at-onset function under etiologic heterogeneity. We use the life-table approach and survival analysis methods. This method is illustrated using data on first-degree relatives of probands from two sets of families with high cancer incidence: one with breast/ovarian cancer and the other with colon cancer. A comparison of the estimated age-at-onset function obtained by the two methods is presented. In both cases, colon cancer as well as breast/ovarian cancer, the estimates of onset probabilities based on proportion of cases, are consistently higher than those obtained by the life-table method. For breast/ovarian cancer, this difference is not as striking as it is in the case of colon cancer; nevertheless, the method using proportion of cases tends to give a lower estimate of the age-at-onset function (higher probability of being affected at lower age) than the life-table approach.     

Evidence for further breast cancer susceptibility genes in addition to BRCA1 and BRCA2 in a population-based study.

We used data from a population based series of breast cancer patients to investigate the genetic models that can best explain familial breast cancer not due to the BRCA1 and BRCA2 genes. The data set consisted of 1,484 women diagnosed with breast cancer under age 55 registered in the East Anglia Cancer registry between 1991-1996. Blood samples taken from the patients were analysed for mutations in BRCA1 and BRCA2. The genetic models were constructed using information on breast and ovarian cancer history in first-degree relatives and on the mutation status of the index patients. We estimated the simultaneous effects of BRCA1, BRCA2, a third hypothetical gene BRCA3, and a polygenic effect. The models were assessed by likelihood comparisons and by comparison of the observed numbers of mutations and affected relatives with the predicted numbers. BRCA1 and BRCA2 could not explain all the familial clustering of breast cancer. The best-fitting single gene model for BRCA3 was a recessive model with a disease allele frequency 24% and penetrance 42% by age 70. However, a polygenic model gave a similarly good fit. The estimated population frequencies for BRCA1 and BRCA2 mutations were similar under both recessive and polygenic models, 0.024 and 0.041%, respectively. A dominant model for BRCA3 gave a somewhat worse fit, although the difference was not significant. The mixed recessive model was identical to the recessive model and the mixed dominant very similar to the polygenic model. The BRCA3 genetic models were robust to the BRCA1 and BRCA2 penetrance assumptions. The overall fit of all models was improved when the known effects of parity on breast and ovarian cancer risks were included in the model-in this case a polygenic model fits best. These findings suggest that a number of common, low-penetrance genes with additive effects may account for the residual non-BRCA1/2 familial aggregation of breast cancer, but Mendelian inheritance of an autosomal recessive allele cannot be ruled out.     

Cost-Effectiveness of Testing for Breast Cancer Susceptibility Genes

Objectives:  Genetic mutations in breast cancer susceptibility genes BRCA1/2 are associated with an increased risk of breast/ovarian cancers. Cost-effective preventive measures are available for women who test positive. The objective of this study was to determine at what risk of mutation it is cost-effective to test women for BRCA1/2 mutations.
Methods:  A semi-Markov model accrued costs and quality-adjusted life years (QALYs) annually from the societal perspective. The estimates of health-care costs, life expectancy, likelihood of obtaining a mastectomy or oophorectomy, and patient preferences for treatment and certainty about their BRCA1/2 status were based on the literature.
Results:  At a 10% probability of mutation (the current guideline), the test strategy generated 22.9 QALYs over the lifetime and cost $118k, while the no-test strategy generated 22.7 QALYs and cost $117k. The incremental cost-effectiveness ratio of the test strategy was $9k and the differences between costs and effects were not substantial. The test strategy remained cost-effective to a probability of mutation of 0%, as long as utility gained from a negative test result was 0.006 or greater. These results were sensitive to the frequency of inconclusive test results and utility gain from a negative test result.
Conclusions:  The costs and effectiveness of both the test and no-test strategies are very similar even when there is a small probability of mutation. Current guidelines, which can be used by insurance companies to refuse coverage, could deny some women a cost-effective approach. Further research to decrease the frequency of inconclusive results could improve the cost-effectiveness of this test.     

Familial ovarian cancer: a population-based case-control study

Data from a multicenter population-based case-control study were analyzed to assess the degree of aggregation of ovarian cancer in families. Included as cases were 493 women aged 20-54 who had been newly diagnosed with epithelial ovarian cancer. The frequency with which cases reported a family history of ovarian cancer was compared with the frequency for a group of 2,465 controls selected by random digit dialing. The odds ratios for ovarian cancer in first- and second-degree relatives were 3.6 (95% confidence interval (Cl) 1.8-7.1) and 2.9 (95% Cl 1.6-5.3), respectively, compared with women with no family history of ovarian cancer. The null hypothesis of no association was excluded on both the maternal and paternal sides of the families studied. Ovarian cancer in relatives was reported by women with malignant lesions but not by women with borderline lesions. These results did not seem to be attributable to the possible confounding effects of any of several covariates or to errors in reporting family history of ovarian cancer.     

BRCA1 R841W: A strong candidate for a common mutation with moderate phenotype

BRCA1 mutations cause increased risk for breast and ovarian cancer, frequently of early onset. Many different mutations occur in BRCA1, including several examples of recurrent mutations, each of which accounts for a significant number of families with heritable cancer predisposition. These common mutations have an etiological role in many breast and ovarian cancer cases and provide the opportunity to examine genotype-phenotype correlations and genotype-environment interactions in individuals with the identical BRCA1 lesion. We report a novel missense change in BRCA1, 2640 C→T (R841W), found in 3 cases from a subject group of 305 breast and 79 ovarian cancer cases from Orange County, CA. These are consecutive, population-based cases not selected for age or family history. In all three cases, there is a strong family history of breast, ovarian, or other cancers possibly related to a BRCA1 defect and family members showed a high concordance of cancer incidence with the presence of R841W. The age of cancer onset was not always distinct from typical sporadic cases. Testing of a sample of 413 unrelated individuals to examine the hypothesis that R841W might be a rare polymorphism detected one additional instance in a woman with breast cancer diagnosed at age 77 years, and cancer in one parent. R841W is likely to be an etiologically significant lesion with involvement in close to 1% (95% confidence interval 0–1.7%) of all breast and ovarian cancers in this population. © 1996 Wiley-Liss, Inc.     

Estimating the number of potential family members eligible for BRCA1 and BRCA2 mutation testing in a “Traceback” approach

U.S. guidelines recommend BRCA1/2 mutation testing for women diagnosed with high‐grade ovarian cancer (HGOC) to increase recognition of carriers, but most remain unidentified and at risk. Accordingly, an approach termed “Traceback” has been proposed in which probands are retrospectively identified by testing archived pathology specimens, and family members are traced to provide genetic counseling and testing. We used population‐based data to estimate the number of family members who might be contacted through such a program. We used incidence data from the Surveillance, Epidemiology, and End Results (SEER) Program to estimate the number of women diagnosed with HGOC from 2005 to 2016, and census data to estimate the number of spouses, offspring, and siblings (both sexes). Using overall survival for HGOC from SEER and all‐cause mortality rates from the Centers for Diseases Control and Prevention, we estimated the number of patients, spouses, offspring, and siblings of HGOC cases living in 2017. Due to the high mortality rate of HGOC, consent from living probands may be possible in only 42% of the cases; consent to test pathology specimens would need to be sought from next of kin for the remainder. In 2017, an estimated 406,919 living next of kin (spouses, siblings, offspring) would be available for potential consent. Testing archived ovarian cancer pathology specimens may enable the identification of BRCA1/2 mutation carriers, but consent from next of kin would be required in in 58% of cases. Although Traceback offers the possibility of identifying unaffected BRCA1/2 mutation carriers, pilot feasibility studies that include assessment of methods to secure consent are needed.     

Association between family history of cancer and breast cancer defined by estrogen and progesterone receptor status

There are recent data to suggest that risk factors for breast cancer may differ according to whether the tumor expresses detectable levels of the estrogen receptor (ER) and progesterone receptor (PR). While a family history of breast cancer is one of the most consistent predictors of the disease, we recently reported a modest inverse association with ER+PR− tumors. However, the definition of a family history of cancer did not consider second-degree relatives or cancer sites that may be etiologically related. The current report presents additional data analysis from the Iowa Women's Health Study, a prospective population-based cohort study conducted among 41,837 postmenopausal women. At baseline in 1986, respondents provided information on family history of cancers of the breast, ovaries, or uterus/endometrium in their mothers, sisters, daughters, maternal and paternal grandmothers, and maternal and paternal aunts. Data on family history of prostate cancer in fathers and brothers and age at onset of breast cancer in mothers and sisters were collected in 1992. Cohort members were followed for cancer incidence through the statewide tumor registry. After 7 years and more than 235,000 person-years of follow-up, 939 incident cases of breast cancer were identified. Information was obtained from the tumor registry on ER (+/−) and PR (+/−) status for 610 cases (65.0%). A family history of breast cancer in first-degree relatives was associated with increased risk (relative risk [RR] = 1.4; 95% confidence interval [CI]: 1.1–1.6) for all receptor-defined subtypes of breast cancer except ER+PR− tumors (RR = 0.7; 95% CI: 0.3–1.4). These results were unchanged when data on second-degree relatives were included. When the onset of breast cancer in relatives occurred at or before the age of 45 years, increased risks were evident only for ER−PR+ and ER−PR− tumors (RR = 2.3 and 3.3, respectively). Conversely, when relatives were affected with breast cancer after the age of 45 years, increased risks were most apparent for ER+PR+ and ER−PR+ tumors (RR = 1.3 and 3.2, respectively). A family history of prostate cancer in first-degree relatives was associated with a 1.2-fold increased risk of breast cancer (95% CI: 0.98–1.50), largely a reflection of the association with ER−PR− tumors (RR = 1.5; 95% CI: 0.8–3.0). The small numbers of cases in some categories and the corresponding wide CIs preclude definitive conclusions, but these data are at least suggestive that joint stratification of breast tumors on ER and PR status may be useful in partitioning breast cancer families into more homogeneous subsets. © 1996 Wiley-Liss, Inc.     

乳腺癌中BRCA1基因突变与雌激素受体的关系

目的探讨遗传性乳腺癌与卵巢癌易感基因(Hereditarybreastandovariancancersusceptibilitygene,BRCA1)基因突变、雌激素受体(Estrogenreceptor,ER)在乳腺癌中的作用以及二者之间的关系。方法选取64例乳腺癌患者标本作研究组,另取10例非癌乳腺组织标本作对照组。利用PCR-SSCP法和直接测序法检测BRCA1基因突变情况;利用SP(链霉菌抗生物素蛋白-过氧化物酶链接法)二步法检测ER,比较ER阳性组与ER阴性组BRCA1突变情况。结果10例非乳腺癌组织未检测出BRCA1基因突变。64例乳腺癌标本中检出BRCA1基因突变6例,突变率为9.4%。突变发生在5、12、17外显子上,均为错义突变,ER阳性44例,阳性率为68.75%(44/64)。ER阳性组中只有1例BRCA1突变(1/44),ER阴性组中有5例检出BRCA1突变(5/20),两组比较BRCA1突变率有显著差异性(P>0.05)。结论广西乳腺癌与BRCA1基因突变有关,BRCA1突变与雌激素受体有关,BRCA1基因突变病人雌激素阴性状态比非BRCA1基因突变病人多。     

Management of a woman with a family history of breast cancer

Recent media publicity about breast cancer has caused concern for many women. Most women with a relative with breast cancer are not at substantially increased risk. NICE released revised guidelines in 2004 classifying women into risk groups. When a woman presents with concerns, it is important to take a full family history. For those that fit into a high-risk group, referral to tertiary care may be appropriate. Genetic testing of BRCA1 and BRCA2 may be offered in families where there is a living affected family member to test first and can be offered to unaffected individuals when there is Ashkenazi Jewish background. Breast management options for those at high risk include breast screening from a young age. MRI screening also appears to be useful. The efficacy of ovarian screening is being studied although it is known that prophylactic oophrectomy before menopause reduces the risk of both breast and ovarian cancer. Prophylactic mastectomy is also an option for these women. Genetic counselling and psychosocial support are important.     

Recall bias in subjective reports of familial cancer

Both twins in a pair in which one had suffered breast cancer (115 pairs) were asked about the occurrence of cancer among first- and second-degree relatives. For all cancer sites together, there was agreement about 129 cases; another 48 cancers were mentioned only by the case twin and another 55 only by the co-twin. For breast cancer, there was agreement about 22 events; another 12 cases were provided by the cancer twin and four by the co-twin. The odds ratio for a family history of cancer was 1.14; for breast cancer the corresponding value was 1.48. The results are suggestive of some recall bias in subjective reports on familial cancer.     

Validation of family history of breast cancer and identification of the BRCA1 and other syndromes using a population-based cancer registry

A major risk factor for breast cancer is family history of the disease in first-degree relatives. This study evaluates the validity of family history information on breast cancer in mothers and sisters of breast cancer probands from the cancer registry (CR) compared to personal interviews (PI) of 359 consecutive population-based cases of breast cancer. Breast cancer is seen in mothers of 14% of probands by CR compared to 12% by PI. Further, 13% of probands have a sister with breast cancer using CR compared to 12% by PI. Using PI as the standard, the sensitivity of the CR family history data in mothers is 92% and the specificity is 99%, while in sisters they are 88% and 99%, respectively. These estimates were calculated on cases where family history information is available in the CR. Sensitivity and specificity are recalculated, recording an “error” whenever family history information is not available, and they are 75% and 68%, respectively, for mothers and 72% and 70%, respectively, for sisters. Estimates of proband-mother and proband-sisters familial breast cancer from CR and PI are sufficiently similar to warrant the use of CR family history data in studies of genetic epidemiology. The family phenotype consistent with the BRCA1 syndrome was found in four (1.1%) probands, all below age 50 years, while for BRCA2 there were five (1.4%) probands, three below age 50 years and two 50 years or older. Site-specific familial breast cancer was found in 23 (6.4%) probands. Population-based multiple-case breast cancer families can rapidly be identified through CR. These families can make substantial contributions to the study of genetic and environmental etiology of the disease as well as benefit from preventive and therapeutic efforts. As new knowledge and tools in molecular genetics become available, there is an urgent need for large population-based registries of families at high risk for cancer. © 1996 Wiley-Liss, Inc.     

Screening of women at high risk for breast cancer

A woman may be at high risk of breast cancer because of a strong family history of breast cancer or because she carries a mutation in the BRCA1 or BRCA2 gene. The annual risk for women in this category is between 1% and 2% and the lifetime risk of breast cancer among gene carriers may approach 80%. Several recent trials have reported that the sensitivity of MRI for imaging breast cancer greatly exceeds that of conventional mammography, but no study has yet determined that annual MRI reduces breast cancer-specific mortality. Women with breast cancer and a BRCA1 mutation typically develop aggressive breast cancers and the prognosis is relatively poor for women with small node-negative breast cancers (compared to non-carriers) in particular, if chemotherapy is not given. It is hoped that annual MRI screening combined with appropriate treatment will result in decreased mortality for this and other groups of high-risk women. MRI-based screening for women at moderate risk is a topic of great interest—MRI has not yet been endorsed in moderate risk women because of the high cost of screening and because the specificity of the screening test is not yet determined in this subgroup.     

418例肺癌患者家族癌症发病史流行病学调查分析

目的 了解肺癌患者中的家族癌症史的流行情况.方法 依据《人群疾病家族史和病史调查表》采用面对面的方式对巴中地区418例肺癌患者家族癌症史进行调查.结果 418例肺癌患者中家族史癌症阳性和肺癌阳性率分别为36.12％(151/418)和28.47％(119/418),两者间阳性率差异无统计学意义(P>0.05).患者家属...     

Practical implementation of frailty models in Mendelian risk prediction

There are numerous statistical models used to identify individuals at high risk of cancer due to inherited mutations. Mendelian models predict future risk of cancer by using family history with estimated cancer penetrances (age- and sex-specific risk of cancer given the genotype of the mutations) and mutation prevalences. However, there is often residual risk heterogeneity across families even after accounting for the mutations in the model, due to environmental or unobserved genetic risk factors. We aim to improve Mendelian risk prediction by incorporating a frailty model that contains a family-specific frailty vector, impacting the cancer hazard function, to account for this heterogeneity. We use a discrete uniform population frailty distribution and implement a marginalized approach that averages each family's risk predictions over the family's frailty distribution. We apply the proposed approach to improve breast cancer prediction in BRCAPRO, a Mendelian model that accounts for inherited mutations in the BRCA1 and BRCA2 genes to predict breast and ovarian cancer. We evaluate the proposed model's performance in simulations and real data from the Cancer Genetics Network and show improvements in model calibration and discrimination. We also discuss alternative approaches for incorporating frailties and their strengths and limitations.