ReClassification of Patients with Ambiguous CA125 for Optimised Pre-Surgical Triage

Pre-surgical clinical assessment of an adnexal mass is a complex process, and ideally requires accurate and rapid identification of disease status. Gold standard biomarker CA125 is extensively used off-label for this purpose; however its performance is typically inadequate, particularly for the detection of early stage disease and discrimination between benign versus malignant status. We recently described a multi-marker panel (MMP) and associated risk index for the differentiation of benign from malignant ovarian disease. In this study we applied a net reclassification approach to assess the use of MMP index to rescue those cases where low CA125 incorrectly excludes cancer diagnoses, or where benign disease is incorrectly assessed as "high risk" due to elevated CA125. Reclassification of such patients is of significant value to assist in the timely and accurate referral for patients where CA125 titer is uninformative.

A Novel Predictive Multi-Marker Test for the Pre-Surgical Identification of Ovarian Cancer

Ovarian cancer remains the most lethal of gynecological malignancies, with the 5-year survival below 50%. Currently there is no simple and effective pre-surgical diagnosis or triage for patients with malignancy, particularly those with early-stage or low-volume tumors. Recently we discovered that CXCL10 can be processed to an inactive form in ovarian cancers and that its measurement has diagnostic significance. In this study we evaluated the addition of processed CXCL10 to a biomarker panel for the discrimination of benign from malignant disease. Multiple biomarkers were measured in retrospectively collected plasma samples (n = 334) from patients diagnosed with benign or malignant disease, and a classifier model was developed using CA125, HE4, Il6 and CXCL10 (active and total). The model provided 95% sensitivity/95% specificity for discrimination of benign from malignant disease. Positive predictive performance exceeded that of "gold standard" scoring systems including CA125, RMI and ROMA% and was independent of menopausal status. In addition, 80% of stage I-II cancers in the cohort were correctly identified using the multi-marker scoring system. Our data suggest the multi-marker panel and associated scoring algorithm provides a useful measurement to assist in pre-surgical diagnosis and triage of patients with suspected ovarian cancer.

Melanoma risk prediction based on a polygenic risk score and clinical risk factors

Melanoma is one of the most commonly diagnosed cancers in the Western world: third in Australia, fifth in the USA and sixth in the European Union. Predicting an individual's personal risk of developing melanoma may aid them in undertaking effective risk reduction measures. The objective of this study was to use the UK Biobank to predict the 10-year risk of melanoma using a newly developed polygenic risk score (PRS) and an existing clinical risk model. We developed the PRS using a matched case-control training dataset ( N  = 16 434) in which age and sex were controlled by design. The combined risk score was developed using a cohort development dataset ( N  = 54 799) and its performance was tested using a cohort testing dataset ( N  = 54 798). Our PRS comprises 68 single-nucleotide polymorphisms and had an area under the receiver operating characteristic curve of 0.639 [95% confidence interval (CI) = 0.618-0.661]. In the cohort testing data, the hazard ratio per SD of the combined risk score was 1.332 (95% CI = 1.263-1.406). Harrell's C-index was 0.685 (95% CI = 0.654-0.715). Overall, the standardized incidence ratio was 1.193 (95% CI = 1.067-1.335). By combining a PRS and a clinical risk score, we have developed a risk prediction model that performs well in terms of discrimination and calibration. At an individual level, information on the 10-year risk of melanoma can motivate people to take risk-reduction action. At the population level, risk stratification can allow more effective population-level screening strategies to be implemented.

Development and validation of a simple prostate cancer risk prediction model based on age, family history, and polygenic risk

BACKGROUND

Accurate prostate cancer risk assessment will enable identification of men who are at increased risk of the disease. Using the UK Biobank population-based cohort, we developed and validated a simple model comprising age, family history, and a polygenic risk score (PRS) to predict 5-year risk of prostate cancer.

METHODS

Eligible participants were unaffected Caucasian men aged 40-69 years at their baseline assessment who had genotyping data available and had completed 6 or more weeks of follow-up. Family history was the number of affected first-degree relatives: 0, 1, or 2+. We used 264 single-nucleotide polymorphisms (SNPs) of a previously developed 269-SNP PRS and population standardized the PRS to have a mean of 1. Age was categorized into 10-year groups: 40-49, 50-59, and 60-69. In a 70% training data set, we used Cox regression with age as the time axis to model family history, PRS, and age group. The model estimates were used with prostate cancer incidences to derive 5-year risks of prostate cancer. Using 5 years of follow-up in a 30% testing data set, the model was tested in terms of its association per quintile of risk, discrimination, and calibration.

RESULTS

Of the 198 334 eligible participants, 8996 (4.5%) were diagnosed with incident prostate cancer during follow-up and had a mean age of 67.9 (SD = 5.8) years at diagnosis. The best-fitting model included the PRS, family history, 10-year age group, interactions between age and PRS, and age and family history. In the 30% testing data set with follow-up limited to 5 years, the hazard ratio per SD of 5-year risk was 3.058 (95% confidence interval [CI], 2.720-3.438) and the Harrell's C-index was 0.811 (95% CI, 0.800-0.821). Overall, there were 1088 observed and 1159.1 expected prostate cancers, a standardized incidence ratio of 0.939 (95% CI, 0.885-0.996).

CONCLUSIONS

Men at increased risk of prostate cancer could benefit from informed discussions around the risks and benefits of available options for screening for prostate cancer. Although the model was developed in Caucasian men, it can be used with ethnicity-specific polygenic risk and incidence rates for other populations.

Validation of a breast cancer risk prediction model based on the key risk factors: family history, mammographic density and polygenic risk

PURPOSE

We compared a simple breast cancer risk prediction model, BRISK (which includes mammographic density, polygenic risk and clinical factors), against a similar model with more risk factors (simplified Rosner) and against two commonly used clinical models (Gail and IBIS).

METHODS

Using nested case-control data from the Nurses' Health Study, we compared the models' association, discrimination and calibration. Classification performance was compared between Gail and BRISK for 5-year risks and between IBIS and BRISK for remaining lifetime risk.

RESULTS

The odds ratio per standard deviation was 1.43 (95% CI 1.32, 1.55) for BRISK 5-year risk, 1.07 (95% CI 0.99, 1.14) for Gail 5-year risk, 1.72 (95% CI 1.59, 1.87) for simplified Rosner 10-year risk, 1.51 (95% CI 1.41, 1.62) for BRISK remaining lifetime risk and 1.26 (95% CI 1.16, 1.36) for IBIS remaining lifetime risk. The area under the receiver operating characteristic curve (AUC) was improved for BRISK over Gail for 5-year risk (AUC = 0.636 versus 0.511, P < 0.0001) and for BRISK over IBIS for remaining lifetime risk (AUC = 0.647 versus 0.571, P < 0.0001). BRISK was well calibrated for the estimation of both 5-year risk (expected/observed [E/O] = 1.03; 95% CI 0.73, 1.46) and remaining lifetime risk (E/O = 1.01; 95% CI 0.86, 1.17). The Gail 5-year risk (E/O = 0.85; 95% CI 0.58, 1.24) and IBIS remaining lifetime risk (E/O = 0.73; 95% CI 0.60, 0.87) were not well calibrated, with both under-estimating risk. BRISK improves classification of risk compared to Gail 5-year risk (NRI = 0.31; standard error [SE] = 0.031) and IBIS remaining lifetime risk (NRI = 0.287; SE = 0.035).

CONCLUSION

BRISK performs better than two commonly used clinical risk models and no worse compared to a similar model with more risk factors.

Validation of an abridged breast cancer risk prediction model for the general population

Accurate breast cancer risk prediction could improve risk-reduction paradigms if thoughtfully employed in clinical practice. Identification of at-risk women is the first step in tailoring risk screening and risk-reduction protocols to women's needs. Using the UK Biobank, we validated a simple risk model to predict breast cancer risk in the general population. Our simple breast cancer risk (BRISK) model integrates a combination of impactful breast cancer-associated risk factors including extended family history and polygenic risk allowing for the removal of moderate factors currently found in comprehensive traditional models. Using two versions of BRISK, differing by 77-SNP versus 313-SNP polygenic risk score integration, we found improved discrimination and risk categorization of both BRISK models compared to one of the most well-known models, the Breast Cancer Risk Assessment Tool (BRCAT). Over a five-year period, at-risk women classified ≥3% 5-year risk by BRISK had a 1.829 (95% CI = 1.710, 1.956) times increased incidence of breast cancer compared to the population, which was higher than the 1.413 (95% CI = 1.217 to 1.640) times increased incidence for women classified ≥3% by BCRAT.

Improvement of a clinical colorectal cancer risk prediction model integrating polygenic risk

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Background: Improving colorectal cancer risk prediction and stratification is pivotal for implementing better screening and prevention programs in public health and for enabling a personalised approach for assessing patients’ colorectal cancer risk. Methods: In this study, we used the UK Biobank to compare the performance of a risk prediction model incorporating two different polygenic risk scores – one comprising 45 SNPs and the other comprising 140 SNPs. The clinical component of the risk prediction model included a simple measure of first-degree family history. We used age- and sex-specific population incidence rates to calculate full-lifetime risks. Results: The model using the 140-SNP PRS showed an improvement in discrimination, calibration and risk stratification over the model using the 45-SNP PRS for full-lifetime risk: discrimination was 0.706 (95% CI 0.697–0.715) and 0.674 (95% CI 0.664–0.683), respectively, and the P for difference was < 0.001. The 140-SNP model was well calibrated and showed a small overestimation of risk 0.951 (95% CI 0.918–0.986). Standard incidence ratios compared to population incidence rates showed that, for the 140-SNP model, the top quintile of risk shows a 27% improvement compared to the 45-SNP model. Furthermore, there was a 3-fold difference in colorectal cancer incidence between adults identified in the top quintile compared to the bottom quintile of risk using the 140-SNP model versus the 45-SNP model. Conclusions: This updated risk prediction score with a 140–SNP PRS and a simple measure of family history, improves risk prediction and risk stratification in the general population compared with a similar model with a 45-SNP PRS, and will ultimately assist in colorectal cancer disease prevention in the clinic.

A combined clinical and genetic model for predicting risk of ovarian cancer

OBJECTIVE

Women with a family history of ovarian cancer or a pathogenic or likely pathogenic gene variant are at high risk of the disease, but very few women have these risk factors. We assessed whether a combined polygenic and clinical risk score could predict risk of ovarian cancer in population-based women who would otherwise be considered as being at average risk.

METHODS

We used the UK Biobank to conduct a prospective cohort study assessing the performance of 10-year ovarian cancer risks based on a polygenic risk score, a clinical risk score and a combined risk score. We used Cox regression to assess association, Harrell's C-index to assess discrimination and Poisson regression to assess calibration.

RESULTS

The combined risk model performed best and problems with calibration were overcome by recalibrating the model, which then had a hazard ratio per quintile of risk of 1.338 [95% confidence interval (CI), 1.152-1.553], a Harrell's C-index of 0.663 (95% CI, 0.629-0.698) and overall calibration of 1.000 (95% CI, 0.874-1.145). In the refined model with estimates based on the entire dataset, women in the top quintile of 10-year risk were at 1.387 (95% CI, 1.086-1.688) times increased risk, while women in the top quintile of full-lifetime risk were at 1.527 (95% CI, 1.187-1.866) times increased risk compared with the population.

CONCLUSION

Identification of women who are at high risk of ovarian cancer can allow healthcare providers and patients to engage in joint decision-making discussions around the risks and benefits of screening options or risk-reducing surgery.

The SCRIPT trial: study protocol for a randomised controlled trial of a polygenic risk score to tailor colorectal cancer screening in primary care

Background

Polygenic risk scores (PRSs) can predict the risk of colorectal cancer (CRC) and target screening more precisely than current guidelines using age and family history alone. Primary care, as a far-reaching point of healthcare and routine provider of cancer screening and risk information, may be an ideal location for their widespread implementation.

Methods

This trial aims to determine whether the SCRIPT intervention results in more risk-appropriate CRC screening after 12 months in individuals attending general practice, compared with standard cancer risk reduction information. The SCRIPT intervention consists of a CRC PRS, tailored risk-specific screening recommendations and a risk report for participants and their GP, delivered in general practice. Patients aged between 45 and 70 inclusive, attending their GP, will be approached for participation. For those over 50, only those overdue for CRC screening will be eligible to participate. Two hundred and seventy-four participants will be randomised to the intervention or control arms, stratified by general practice, using a computer-generated allocation sequence. The primary outcome is risk-appropriate CRC screening after 12 months. For those in the intervention arm, risk-appropriate screening is defined using PRS-derived risk; for those in the control arm, it is defined using family history and national screening guidelines. Timing, type and results of the previous screening are considered in both arms. Objective health service data will capture screening behaviour. Secondary outcomes include cancer-specific worry, risk perception, predictors of CRC screening behaviour, screening intentions and health service use at 1, 6 and 12 months post-intervention delivery.

Discussion

This trial aims to determine whether a PRS-derived personalised CRC risk estimate delivered in primary care increases risk-appropriate CRC screening. A future population risk-stratified CRC screening programme could incorporate risk assessment within primary care while encouraging adherence to targeted screening recommendations.

Trial registration

Australian and New Zealand Clinical Trial Registry ACTRN12621000092897p. Registered on 1 February 2021.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13063-022-06734-7.

Validation of a clinical and genetic model for predicting severe COVID-19

Using nested case–control data from the Lifelines COVID-19 cohort, we undertook a validation study of a clinical and genetic model to predict the risk of severe COVID-19 in people with confirmed COVID-19 and in people with confirmed or self-reported COVID-19. The model performed well in terms of discrimination of cases and controls for all ages (area under the receiver operating characteristic curve (AUC) = 0.680 for confirmed COVID-19 and AUC = 0.689 for confirmed and self-reported COVID-19) and in the age group in which the model was developed (50 years and older; AUC = 0.658 for confirmed COVID-19 and AUC = 0.651 for confirmed and self-reported COVID-19). There was no evidence of over- or under-dispersion of risk scores but there was evidence of overall over-estimation of risk in all analyses (all P < 0.0001). In the light of large numbers of people worldwide remaining unvaccinated and continuing uncertainty regarding vaccine efficacy over time and against variants of concern, identification of people at high risk of severe COVID-19 may encourage the uptake of vaccinations (including boosters) and the use of non-pharmaceutical inventions.

Polygenic risk scores for cardiovascular diseases and type 2 diabetes

Polygenic risk scores (PRSs) are a promising approach to accurately predict an individual's risk of developing disease. The area under the receiver operating characteristic curve (AUC) of PRSs in their population are often only reported for models that are adjusted for age and sex, which are known risk factors for the disease of interest and confound the association between the PRS and the disease. This makes comparison of PRS between studies difficult because the genetic effects cannot be disentangled from effects of age and sex (which have a high AUC without the PRS). In this study, we used data from the UK Biobank and applied the stacked clumping and thresholding method and a variation called maximum clumping and thresholding method to develop PRSs to predict coronary artery disease, hypertension, atrial fibrillation, stroke and type 2 diabetes. We created case-control training datasets in which age and sex were controlled by design. We also excluded prevalent cases to prevent biased estimation of disease risks. The maximum clumping and thresholding PRSs required many fewer single-nucleotide polymorphisms to achieve almost the same discriminatory ability as the stacked clumping and thresholding PRSs. Using the testing datasets, the AUCs for the maximum clumping and thresholding PRSs were 0.599 (95% confidence interval [CI]: 0.585, 0.613) for atrial fibrillation, 0.572 (95% CI: 0.560, 0.584) for coronary artery disease, 0.585 (95% CI: 0.564, 0.605) for type 2 diabetes, 0.559 (95% CI: 0.550, 0.569) for hypertension and 0.514 (95% CI: 0.494, 0.535) for stroke. By developing a PRS using a dataset in which age and sex are controlled by design, we have obtained true estimates of the discriminatory ability of the PRSs alone rather than estimates that include the effects of age and sex.

Development and validation of a clinical and genetic model for predicting risk of severe COVID-19

Clinical and genetic risk factors for severe coronavirus disease 2019 (COVID-19) are often considered independently and without knowledge of the magnitudes of their effects on risk. Using severe acute respiratory syndrome-coronavirus-2 (SARS-CoV-2) positive participants from the UK Biobank, we developed and validated a clinical and genetic model to predict risk of severe COVID-19. We used multivariable logistic regression on a 70% training dataset and used the remaining 30% for validation. We also validated a previously published prototype model. In the validation dataset, our new model was associated with severe COVID-19 (odds ratio per quintile of risk = 1.77, 95% confidence interval (CI) 1.64-1.90) and had acceptable discrimination (area under the receiver operating characteristic curve = 0.732, 95% CI 0.708-0.756). We assessed calibration using logistic regression of the log odds of the risk score, and the new model showed no evidence of over- or under-estimation of risk (α = -0.08; 95% CI -0.21-0.05) and no evidence or over-or under-dispersion of risk (β = 0.90, 95% CI 0.80-1.00). Accurate prediction of individual risk is possible and will be important in regions where vaccines are not widely available or where people refuse or are disqualified from vaccination, especially given uncertainty about the extent of infection transmission among vaccinated people and the emergence of SARS-CoV-2 variants of concern.

An integrated clinical and genetic model for predicting risk of severe COVID-19: A population-based case-control study

Up to 30% of people who test positive to SARS-CoV-2 will develop severe COVID-19 and require hospitalisation. Age, gender, and comorbidities are known to be risk factors for severe COVID-19 but are generally considered independently without accurate knowledge of the magnitude of their effect on risk, potentially resulting in incorrect risk estimation. There is an urgent need for accurate prediction of the risk of severe COVID-19 for use in workplaces and healthcare settings, and for individual risk management. Clinical risk factors and a panel of 64 single-nucleotide polymorphisms were identified from published data. We used logistic regression to develop a model for severe COVID-19 in 1,582 UK Biobank participants aged 50 years and over who tested positive for the SARS-CoV-2 virus: 1,018 with severe disease and 564 without severe disease. Model discrimination was assessed using the area under the receiver operating characteristic curve (AUC). A model incorporating the SNP score and clinical risk factors (AUC = 0.786; 95% confidence interval = 0.763 to 0.808) had 111% better discrimination of disease severity than a model with just age and gender (AUC = 0.635; 95% confidence interval = 0.607 to 0.662). The effects of age and gender are attenuated by the other risk factors, suggesting that it is those risk factors–not age and gender–that confer risk of severe disease. In the whole UK Biobank, most are at low or only slightly elevated risk, but one-third are at two-fold or more increased risk. We have developed a model that enables accurate prediction of severe COVID-19. Continuing to rely on age and gender alone (or only clinical factors) to determine risk of severe COVID-19 will unnecessarily classify healthy older people as being at high risk and will fail to accurately quantify the increased risk for younger people with comorbidities.

Implementing physically active learning: Future directions for research, policy, and practice

PURPOSE

To identify co-produced multi-stakeholder perspectives important for successful widespread physically active learning (PAL) adoption and implementation.

METHODS

A total of 35 stakeholders (policymakers n = 9; commercial education sector, n = 8; teachers, n = 3; researchers, n = 15) attended a design thinking PAL workshop. Participants formed 5 multi-disciplinary groups with at least 1 representative from each stakeholder group. Each group, facilitated by a researcher, undertook 2 tasks: (1) using Post-it Notes, the following question was answered: within the school day, what are the opportunities for learning combined with movement? and (2) structured as a washing-line task, the following question was answered: how can we establish PAL as the norm? All discussions were audio-recorded and transcribed. Inductive analyses were conducted by 4 authors. After the analyses were complete, the main themes and subthemes were assigned to 4 predetermined categories: (1) PAL design and implementation, (2) priorities for practice, (3) priorities for policy, and (4) priorities for research.

RESULTS

The following were the main themes for PAL implementation: opportunities for PAL within the school day, delivery environments, learning approaches, and the intensity of PAL. The main themes for the priorities for practice included teacher confidence and competence, resources to support delivery, and community of practice. The main themes for the policy for priorities included self-governance, the Office for Standards in Education, Children's Services, and Skill, policy investment in initial teacher training, and curriculum reform. The main themes for the research priorities included establishing a strong evidence base, school-based PAL implementation, and a whole-systems approach.

CONCLUSION

The present study is the first to identify PAL implementation factors using a combined multi-stakeholder perspective. To achieve wider PAL adoption and implementation, future interventions should be evidence based and address implementation factors at the classroom level (e.g., approaches and delivery environments), school level (e.g., communities of practice), and policy level (e.g., initial teacher training).

The Right to Write: Who 'Owns' the Case Report?

In this Letter to the Editor, Agrawal et al. debate the conflicts that can arise regarding the authorship of case reports. Like all other medical journals, EJCRIM has zero tolerance for the willful undisclosed re-submission of papers that have already been published elsewhere. However, this may occasionally happen by accident, especially in large healthcare institutions in which multiple teams of physicians may care for a patient throughout their illness. EJCRIM endorses and recommends to all potential authors the very sensible suggestions made by Agrawal et al. to avoid such an error occurring. EJCRIM would also encourage authors to consider the following: The first author should ensure that no one else involved in the case has reported it or plans to report it. This is especially important for physicians working in large healthcare centres, and/or for case reports of patients who have been under investigation or treatment for prolonged periods.On rare occasions EJCRIM will consider a case that has already been published, provided that this is fully and explicitly disclosed, and there is a clear reason why re-publication is justified. An example might be where new information has come to light that significantly changes the conclusions of the original report. As in all reports published by EJCRIM the decision to publish will depend on the educational value, or learning points, of the case.

Validation of a genetic risk score for Arkansas women of color

African American women in the state of Arkansas have high breast cancer mortality rates. Breast cancer risk assessment tools developed for African American underestimate breast cancer risk. Combining African American breast cancer associated single-nucleotide polymorphisms (SNPs) into breast cancer risk algorithms may improve individualized estimates of a woman's risk of developing breast cancer and enable improved recommendation of screening and chemoprevention for women at high risk. The goal of this study was to confirm with an independent dataset consisting of Arkansas women of color, whether a genetic risk score derived from common breast cancer susceptibility SNPs can be combined with a clinical risk estimate provided by the Breast Cancer Risk Assessment Tool (BCRAT) to produce a more accurate individualized breast cancer risk estimate. A population-based cohort of African American women representative of Arkansas consisted of 319 cases and 559 controls for this study. Five-year and lifetime risks from the BCRAT were measured and combined with a risk score based on 75 independent susceptibility SNPs in African American women. We used the odds ratio (OR) per adjusted standard deviation to evaluate the improvement in risk estimates produced by combining the polygenic risk score (PRS) with 5-year and lifetime risk scores estimated using BCRAT. For 5-year risk OR per standard deviation increased from 1.84 to 2.08 with the addition of the polygenic risk score and from 1.79 to 2.07 for the lifetime risk score. Reclassification analysis indicated that 13% of cases had their 5-year risk increased above the 1.66% guideline threshold (NRI = 0.020 (95% CI -0.040, 0.080)) and 6.3% of cases had their lifetime risk increased above the 20% guideline threshold by the addition of the polygenic risk score (NRI = 0.034 (95% CI 0.000, 0.070)). Our data confirmed that discriminatory accuracy of BCRAT is improved for African American women in Arkansas with the inclusion of specific SNP breast cancer risk alleles.

Bridging the Data Gap in Breast Cancer Risk Assessment to Enable Widespread Clinical Implementation across the Multiethnic Landscape of the US

Breast cancer remains the second leading cause of cancer death among women and is the most commonly diagnosed cancer in women. Breast cancer risk assessment has been clinically available for nearly 30 years yet is under-utilized in practice for multiple reasons. Incorporation of polygenic risk as well as breast density measurements, promise to increase the accuracy of risk assessment. With that comes the hope that both prevention and screening become more personalized and thus more effective. Incidence rates have been static over the past 15 years and have even increased slightly in African American and Asian/Pacific Islander populations despite the robust data on breast cancer risk reduction measures that exist. Current challenges in reducing breast cancer incidence begin with robust data curation that allows for appropriate risk stratification across our multiethnic population and conclude with the implementation of prevention strategies within our fractured healthcare system.

Adhesion Molecules in Melanoma—More than Just Superglue?

Malignant melanoma is increasing in incidence, and, though early lesions are readily treatable, systemic therapy for metastatic disease remains disappointing. Integrins are a family of cell-surface molecules that mediate adhesion between the cell and the extracellular matrix. One member of the integrin family, the αvβ3 integrin, is associated with progression of melanomas, in that the most malignant cells express the highest levels of αvβ3. Like many members of the integrin family, αvβ3 recognizes the sequence Arg-Gly-Asp (RGD) in its ligands, and other molecules that contain this sequence will compete with the natural ligands (such as vitronectin) for binding. There is growing evidence that integrins function as receptors for signal transduction, and that integrin-mediated signalling can affect cell behaviour and even cell survival. Under certain circumstances, loss of integrin-mediated signalling will induce apoptosis, or programmed cell death, and we have demonstrated that melanoma cells treated with a cyclic peptide with high affinity for the αvβ3 integrin will undergo apoptosis within three days. This mechanism might be exploited therapeutically.

Breast Cancer Risk Prediction Using Clinical Models and 77 Independent Risk-Associated SNPs for Women Aged Under 50 Years: Australian Breast Cancer Family Registry

BACKGROUND

The extent to which clinical breast cancer risk prediction models can be improved by including information on known susceptibility SNPs is not known.

METHODS

Using 750 cases and 405 controls from the population-based Australian Breast Cancer Family Registry who were younger than 50 years at diagnosis and recruitment, respectively, Caucasian and not BRCA1 or BRCA2 mutation carriers, we derived absolute 5-year risks of breast cancer using the BOADICEA, BRCAPRO, BCRAT, and IBIS risk prediction models and combined these with a risk score based on 77 independent risk-associated SNPs. We used logistic regression to estimate the OR per adjusted SD for log-transformed age-adjusted 5-year risks. Discrimination was assessed by the area under the receiver operating characteristic curve (AUC). Calibration was assessed using the Hosmer-Lemeshow goodness-of-fit test. We also constructed reclassification tables and calculated the net reclassification improvement.

RESULTS

The ORs for BOADICEA, BRCAPRO, BCRAT, and IBIS were 1.80, 1.75, 1.67, and 1.30, respectively. When combined with the SNP-based score, the corresponding ORs were 1.96, 1.89, 1.80, and 1.52. The corresponding AUCs were 0.66, 0.65, 0.64, and 0.57 for the risk prediction models, and 0.70, 0.69, 0.66, and 0.63 when combined with the SNP-based score.

CONCLUSIONS

By combining a 77 SNP-based score with clinical models, the AUC for predicting breast cancer before age 50 years improved by >20%.

IMPACT

Our estimates of the increased performance of clinical risk prediction models from including genetic information could be used to inform targeted screening and prevention.

SNPs and breast cancer risk prediction for African American and Hispanic women

For African American or Hispanic women, the extent to which clinical breast cancer risk prediction models are improved by including information on susceptibility single nucleotide polymorphisms (SNPs) is unknown, even though these women comprise increasing proportions of the US population and represent a large proportion of the world’s population. We studied 7539 African American and 3363 Hispanic women from the Women’s Health Initiative. The age-adjusted 5-year risks from the BCRAT and IBIS risk prediction models were measured and combined with a risk score based on >70 independent susceptibility SNPs. Logistic regression, adjusting for age group, was used to estimate risk associations with log-transformed age-adjusted 5-year risks. Discrimination was measured by the odds ratio (OR) per standard deviation (SD) and the area under the receiver operator curve (AUC). When considered alone, the ORs for African American women were 1.28 for BCRAT, and 1.04 for IBIS. When combined with the SNP risk score (OR 1.23), the corresponding ORs were 1.39 and 1.22. For Hispanic women the corresponding ORs were 1.25 for BCRAT, and 1.15 for IBIS. When combined with the SNP risk score (OR 1.39), the corresponding ORs were 1.48 and 1.42. There was no evidence that any of the combined models were not well calibrated. Including information on known breast cancer susceptibility loci provides approximately 10 and 19 % improvement in risk prediction using BCRAT for African Americans and Hispanics, respectively. The corresponding figures for IBIS are approximately 18 and 26 %, respectively.

Abstract P6-09-05: Value of adding single-nucleotide polymorphism panel markers to phenotypic algorithms of breast cancer risk

Currently, breast cancer risk prediction algorithms incorporate phenotypic risk factors, including age, family history, reproductive history and benign breast disease.

Since 2007, genome-wide association studies have identified a growing number of single-nucleotide polymorphisms (SNPs) that are associated with an increased risk of breast cancer. While no single SNP is very informative on its own, a polygenic approach to genetic screening could improve estimates of individual risk, creating the possibility of screening strategies individually tailored to each woman.

We studied cases and controls recruited to the Australian Breast Cancer Family Registry, to investigate whether a SNP risk score derived from a panel of 77 SNPs can improve risk estimates obtained from the commonly used breast cancer risk prediction models (BCRAT, IBIS, BRCAPRO and BOADICEA).

SNP risk scores were calculated using previously published Odds Ratios (ORs) and risk-allele frequencies based on the assumption of independence of additive risks on the log OR scale. SNP risk scores were calculated by multiplying adjusted risk scores for each of the SNPs. Combined risk scores were calculated by multiplying the SNP risk score and the algorithm derived risk scores, under the assumption of independence.

Overall, the inclusion of data on 77 SNPs improved the area under the receiver operating characteristic curve (AUC) for all of the breast cancer risk prediction models: Preliminary data analysis provided AUC values as follows: BCRAT+SNP = 0.656, IBIS+SNP= 0.628, BRCAPRO+SNP= 0.689, BOADICEA+SNP= 0.698.

The breast cancer risk prediction models examined place different weighting on the phenotypic components. For example, the IBIS model is weighted towards uncommon high-risk phenotypes, while the BCRAT is weighted towards lower risks in the general population. A combination of the 77 SNP score and the most appropriate model might substantially improve the ability to identify high-risk women in different screening populations.

Citation Format: Gillian Dite, Richard Allman, John L Hopper. Value of adding single-nucleotide polymorphism panel markers to phenotypic algorithms of breast cancer risk [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P6-09-05.

Economic evaluation of using a genetic test to direct breast cancer chemoprevention in white women with a previous breast biopsy

BACKGROUND

Tamoxifen therapy reduces the risk of breast cancer but increases the risk of serious adverse events including endometrial cancer and thromboembolic events.

OBJECTIVES

The cost effectiveness of using a commercially available breast cancer risk assessment test (BREVAGen™) to inform the decision of which women should undergo chemoprevention by tamoxifen was modeled in a simulated population of women who had undergone biopsies but had no diagnosis of cancer.

METHODS

A continuous time, discrete event, mathematical model was used to simulate a population of white women aged 40-69 years, who were at elevated risk for breast cancer because of a history of benign breast biopsy. Women were assessed for clinical risk of breast cancer using the Gail model and for genetic risk using a panel of seven common single nucleotide polymorphisms. We evaluated the cost effectiveness of using genetic risk together with clinical risk, instead of clinical risk alone, to determine eligibility for 5 years of tamoxifen therapy. In addition to breast cancer, the simulation included health states of endometrial cancer, pulmonary embolism, deep-vein thrombosis, stroke, and cataract. Estimates of costs in 2012 US dollars were based on Medicare reimbursement rates reported in the literature and utilities for modeled health states were calculated as an average of utilities reported in the literature. A 50-year time horizon was used to observe lifetime effects including survival benefits.

RESULTS

For those women at intermediate risk of developing breast cancer (1.2-1.66 % 5-year risk), the incremental cost-effectiveness ratio for the combined genetic and clinical risk assessment strategy over the clinical risk assessment-only strategy was US$47,000, US$44,000, and US$65,000 per quality-adjusted life-year gained, for women aged 40-49, 50-59, and 60-69 years, respectively (assuming a price of US$945 for genetic testing). Results were sensitive to assumptions about patient adherence, utility of life while taking tamoxifen, and cost of genetic testing.

CONCLUSIONS

From the US payer's perspective, the combined genetic and clinical risk assessment strategy may be a moderately cost-effective alternative to using clinical risk alone to guide chemoprevention recommendations for women at intermediate risk of developing breast cancer.

Abstract P2-12-08: Genetic testing for breast cancer risk estimation: A cost-effectiveness analysis

Genetic testing based on seven single-nucleotide polymorphisms (7SNP) can improve individualized estimates of lifetime risk of breast cancer relative to the Gail risk test alone, for the purpose of recommending MRI screening for women at high risk.

An individual-based, continuous-time simulation model of breast cancer and health care processes was used to simulate women in a virtual trial comparing the use of the 7SNP test to the Gail risk test alone to categorize patients as either low risk or high risk. Low risk patients received annual mammogram, while high risk patients received annual MRI.

Cancer incidence was based on Surveillance, Epidemiology, and End Results (SEER) data and validated to the Cancer Prevention Study II (CPS-II) Nutrition Cohort data set. Risk factors are drawn from the National Health and Nutrition Examination Survey (NHANES-4) and Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO) data sets. Mammogram characteristics were derived from the Breast Cancer Surveillance Consortium (BCSC) dataset. Other parameters were derived from published literature.

The 7SNP test (vs Gail alone) saved 0.00734 quality-adjusted life-years (QALYs) per person at a cost of $1,971 per person ($268,386 per QALY). Limiting the 7SNP test to only those patients with a lifetime Gail risk of 16 - 28% resulted in a cost of $163,264 per QALY. These results were sensitive to the age at which the test is given, the discount rate, and the costs of the genetic test and MRI.

The cost-effectiveness of using the 7SNP test for patients with intermediate Gail risk is similar to that of other recommended strategies, including annual MRI for patients with a lifetime risk greater than 20% or BRCA1/2 mutations.

Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr P2-12-08.

Unintentional weight loss predicts decline in activities of daily living function and life-space mobility over 4 years among community-dwelling older adults

BACKGROUND

The relationship between body mass index (BMI), weight loss, and changes in activities of daily living (ADL) function and mobility in older adults is not clear. We sought to study the relationship between BMI and weight loss on the rate of decline in ADL function and life-space mobility over a 4-year period among older African Americans and whites.

METHODS

The participants were 983 enrollees in the University of Alabama at Birmingham (UAB) Study of Aging, a longitudinal study of mobility among community-dwelling older adults stratified to achieve a balanced sample in terms of sex, race, and residence. Primary outcome measures were changes in ADL function and mobility assessed by the UAB Study of Aging Life-Space Assessment (LSA) which were measured every 6 months.

RESULTS

Relative to normal weight participants, those with BMI levels in the obese range did not show more rapid ADL functional decline, but a history of unintentional weight loss predicted more rapid decline. Relative to normal-weight participants, other BMI categories were not associated with more rapid decline in LSA scores. However, unintentional weight loss predicted more rapid declines in LSA. Intentional weight loss had no relation to ADL function or LSA decline.

CONCLUSIONS

In this population of community-dwelling older African Americans and whites, neither BMI nor intentional weight loss had an association with rate of functional decline. Unintentional weight loss had a negative relation with rate of functional decline, regardless of baseline BMI. Whether this is causal remains to be determined.

Leisure-Time Physical Activity and Health-Care Utilization in Older Adults

This study examined whether leisure-time physical activity (LTPA) was associated with health-care utilization in a racially diverse sample of rural and urban older adults. Community-dwelling adults (N= 1,000, 75.32 ± 6.72 years old) self-reported participating in LTPA and their use of the health-care system (physician visits, number and length of hospitalizations, and emergency-room visits). After controlling for variables associated with health and health-care utilization, older adults who reported lower levels of LTPA also reported a greater number of nights in the hospital in the preceding year. There was no support, however, for a relationship between LTPA and the other indicators of health-care utilization. Our findings suggest that being physically active might translate to a quicker recovery for older adults who are hospitalized. Being physically active might not only have health benefits for older persons but also lead to lower health-care costs.

A phase-1 study of sequential mitomycin C and 5-aminolaevulinic acid-mediated photodynamic therapy in recurrent superficial bladder carcinoma

OBJECTIVE

To report a phase-1 study of patients with recurrent superficial bladder cancer treated with photodynamic therapy (PDT) using sequential mitomycin C and 5-aminolaevulinic acid (ALA).

PATIENTS AND METHODS

Twenty-four patients were treated, the primary endpoint being the safety and tolerability of combined therapy at increasing doses of ALA and light.

RESULTS

Mitomycin C instillation was followed by ALA concentrations of 6%, 8% or 10%; there was no effect on toxicity. The light dose, at a wavelength of 635 nm, was increased from zero to 25 J/cm(2), with the upper fluences producing transient symptoms. There were no episodes of skin photosensitivity or systemic toxicity. A total fluence of 25 J/cm(2) represented the upper light dose for the tolerability of this procedure by patients. There were no persistently high urinary symptom scores or reduction in functional bladder capacity up to > or =24 months of follow-up. In this group, cumulative tumour recurrences were none at 4, two at 8, six at 12, nine at 18 and 11 at 24 months after PDT, respectively.

CONCLUSION

Sequential mitomycin C and ALA-PDT is a safe and well tolerated treatment, with potential for managing difficult-to-control superficial transitional cell carcinoma and carcinoma in situ of the bladder.

Investigation of sequential mitomycin C and photodynamic therapy in a mitomycin-resistant bladder cancer cell-line model

OBJECTIVES

To investigate the hypothesis that sequential mitomycin C and 5-aminolaevulinic acid (ALA)-mediated photodynamic therapy (PDT) interact additively in both the J82 bladder cancer cell line and its mitomycin-C-resistant derivative, J82/MMC, and to assess the theoretical basis of this interaction by measuring the relative mitochondrial density of the respective cell lines, on the basis that the mitochondria are the intracellular site where ALA is metabolized to the active photosensitizer, protoporphyrin IX.

MATERIALS AND METHODS

Cell survival was assayed in J82 cell line and the J82/MMC derivative after treating them with sequential ALA-mediated PDT and mitomycin C, and with the sequence of treatments reversed. Cell survival was estimated using the tetrazolium assay. The relative mitochondrial density of the two cell lines was estimated using flow cytometry to measure 123rhodamine fluorescence.

RESULTS

The effect of sequential mitomycin C followed by ALA-mediated PDT enhanced the effect of PDT in both cell lines. In J82/MMC this effect was marginally supra-additive. When ALA-mediated PDT was administered before mitomycin C, the combined effect was 'sub-additive'. 123Rhodamine fluorescence was > 10 times greater in J82/MMC than J82, suggesting a significantly higher mitochondrial density in the former than the latter.

CONCLUSION

Mitomycin C appears to enhance ALA-mediated PDT when administered first. This appears to be particularly so in J82/MMC. This phenomenon may have clinical significance in recurrent superficial bladder cancer.

Delayed expression of apoptosis in human lymphoma cells undergoing low-dose taxol-induced mitotic stress

The links between low-dose range taxol-induced mitotic arrest and the subsequent engagement of apoptosis are important for identifying the routes to therapeutic action. Here we have investigated the timing of cell-cycle perturbation and cell death responses following continuous exposure to clinically relevant drug concentrations (1-20 nM). Following 8 h of exposure to taxol, the cell line DoHH2 (p53 wild type) exhibited mitotic arrest and engagement of apoptosis, whereas the cell line SU-DHL-4 (p53 mutant) breached cell-cycle arrest with progression to an abnormal cycle and a 24 h delay in the engagement of apoptosis. Imaging showed equivalent dysfunction of mitotic spindles in both cell lines. The results of kinetic analyses indicated that although cell death may occur at different stages of progression through mitosis and subsequent cell cycles, the overall kinetics of cell death relate to the rate of arrival at a critical event window in the cell cycle. We propose a simple model of low-dose taxol-induced cell death for cycling populations in which mitotic stress acts as a primary trigger for apoptosis with equivalent but potentially delayed outcomes. This view provides a rationale for the clinical effectiveness of this agent, independent of the initial capacity of the tumour cell to engage apoptosis due, for example, to mutant p53 expression. The results provide a perspective for the design of combination regimens that include low-dose taxol and a component that may disturb mitotic delivery.

Quality of care for hospitalized medicare patients at risk for pressure ulcers

BACKGROUND

No state peer review organization has attempted to identify processes of care related to pressure ulcer prediction and prevention in US hospitals.

OBJECTIVE

To profile and evaluate the processes of care for Medicare patients hospitalized at risk for pressure ulcer development by means of the Medicare Quality Indicator System pressure ulcer prediction and prevention module.

METHODS

A multicenter retrospective cohort study with medical record abstraction was used to obtain a total of 2425 patients aged 65 years and older discharged from acute care hospitals after treatment for pneumonia, cerebrovascular disease, or congestive heart failure. Six processes of care for prevention of pressure ulcers were evaluated: use of daily skin assessment; use of a pressure-reducing device; documentation of being at risk; repositioning for a minimum of 2 hours; nutritional consultation initiated for patients with nutritional risk factors; and staging of pressure ulcer. The associations between processes of care and incidence of pressure ulcer were determined with Kaplan-Meier survival analyses.

RESULTS

National estimates of compliance with process of care were as follows: use of daily skin assessment, 94%; use of pressure-reducing device, 7.5%; documentation of being at risk, 22.6%; repositioning for a minimum of 2 hours, 66.2%; nutritional consultation, 34.3%; stage 1 pressure ulcer staged, 20.2%; and stage 2 or greater ulcer staged, 30.9%.

CONCLUSION

These results suggest that US hospitals and physicians have numerous opportunities to improve care related to pressure ulcer prediction and prevention.