Improving the Detection of Potential Cases of Familial Hypercholesterolemia: Could Machine Learning Be Part of the Solution?

Background: Familial hypercholesterolemia (FH), while highly prevalent, is a significantly underdiagnosed monogenic disorder. Improved detection could reduce the large number of cardiovascular events attributable to poor case finding. We aimed to assess whether machine learning algorithms outperform clinical diagnostic criteria (signs, history, and biomarkers) and the recommended screening criteria in the United Kingdom in identifying individuals with FH-causing variants, presenting a scalable screening criteria for general populations. Methods and results: Analysis included UK Biobank participants with whole exome sequencing, classifying them as having FH when (likely) pathogenic variants were detected in their LDLR, APOB, or PCSK9 genes. Data were stratified into 3 data sets for (1) feature importance analysis; (2) deriving state-of-the-art statistical and machine learning models; (3) evaluating models' predictive performance against clinical diagnostic and screening criteria: Dutch Lipid Clinic Network, Simon Broome, Make Early Diagnosis to Prevent Early Death, and Familial Case Ascertainment Tool. One thousand and three of 454 710 participants were classified as having FH. A Stacking Ensemble model yielded the best predictive performance (sensitivity, 74.93%; precision, 0.61%; accuracy, 72.80%, area under the receiver operating characteristic curve, 79.12%) and outperformed clinical diagnostic criteria and the recommended screening criteria in identifying FH variant carriers within the validation data set (figures for Familial Case Ascertainment Tool, the best baseline model, were 69.55%, 0.44%, 65.43%, and 71.12%, respectively). Our model decreased the number needed to screen compared with the Familial Case Ascertainment Tool (164 versus 227). Conclusions: Our machine learning-derived model provides a higher pretest probability of identifying individuals with a molecular diagnosis of FH compared with current approaches. This provides a promising, cost-effective scalable tool for implementation into electronic health records to prioritize potential FH cases for genetic confirmation.FCT-Fundação para a Ciência e Tecnologia do Ministério da Ciência, Tecnologia e Ensino Superior (SFRH/BD/108503/2015).info:eu-repo/semantics/publishedVersio

Carbohydrates, glycemic index, glycemic load, sugars and breast cancer risk: a systematic review and dose-response meta-analysis of prospective studies

Context: The investigation of dose–response associations between carbohydrate intake, glycemic index, glycemic load, and risk of breast cancer stratified by menopausal status, hormone receptor status, and body mass index (BMI) remains inconclusive. Objective: A systematic review and dose–response meta-analyses was conducted to investigate these associations. Data Sources: As part of the World Cancer Research Fund/American Institute for Cancer Research Continuous Update Project, PubMed was searched up to May 2015 for relevant studies on these associations. Study Selection: Prospective studies reporting associations between carbohydrate intake, glycemic index, or glycemic load and breast cancer risk were included. Data Extraction: Two investigators independently extracted data from included studies. Results: Random-effects models were used to summarize relative risks (RRs) and 95%CIs. Heterogeneity between subgroups, including menopausal status, hormone receptor status, and BMI was explored using meta-regression. Nineteen publications were included. The summary RRs (95%CIs) for breast cancer were 1.04 (1.00–1.07) per 10 units/d for glycemic index, 1.01 (0.98–1.04) per 50 units/d for glycemic load, and 1.00 (0.96–1.05) per 50 g/d for carbohydrate intake. For glycemic index, the association appeared slightly stronger among postmenopausal women (summary RR per 10 units/d, 1.06; 95%CI, 1.02–1.10) than among premenopausal women, though the difference was not statistically significant (Pheterogeneity = 0.15). Glycemic load and carbohydrate intake were positively associated with breast cancer among postmenopausal women with estrogen-negative tumors (summary RR for glycemic load, 1.28; 95%CI, 1.08–1.52; and summary RR for carbohydrates, 1.13; 95%CI, 1.02–1.25). No differences in BMI were detected. Conclusions: Menopausal and hormone receptor status, but not BMI, might be potential influencing factors for the associations between carbohydrate intake, glycemic index, glycemic load, and breast cancer

Improving the Detection of Potential Cases of Familial Hypercholesterolemia: Could Machine Learning Be Part of the Solution?

BACKGROUND: Familial hypercholesterolemia (FH), while highly prevalent, is a significantly underdiagnosed monogenic disorder. Improved detection could reduce the large number of cardiovascular events attributable to poor case finding. We aimed to assess whether machine learning algorithms outperform clinical diagnostic criteria (signs, history, and biomarkers) and the recommended screening criteria in the United Kingdom in identifying individuals with FH-causing variants, presenting a scalable screening criteria for general populations. METHODS AND RESULTS: Analysis included UK Biobank participants with whole exome sequencing, classifying them as having FH when (likely) pathogenic variants were detected in their LDLR, APOB, or PCSK9 genes. Data were stratified into 3 data sets for (1) feature importance analysis; (2) deriving state-of-the-art statistical and machine learning models; (3) evaluating models’ predictive performance against clinical diagnostic and screening criteria: Dutch Lipid Clinic Network, Simon Broome, Make Early Diagnosis to Prevent Early Death, and Familial Case Ascertainment Tool. One thousand and three of 454710 participants were classified as having FH. A Stacking Ensemble model yielded the best predictive performance (sensitivity, 74.93%; precision, 0.61%; accuracy, 72.80%, area under the receiver operating characteristic curve, 79.12%) and outperformed clinical diagnostic criteria and the recommended screening criteria in identifying FH variant carriers within the validation data set (figures for Familial Case Ascertainment Tool, the best baseline model, were 69.55%, 0.44%, 65.43%, and 71.12%, respectively). Our model decreased the number needed to screen compared with the Familial Case Ascertainment Tool (164 versus 227). CONCLUSIONS: Our machine learning–derived model provides a higher pretest probability of identifying individuals with a molecular diagnosis of FH compared with current approaches. This provides a promising, cost-effective scalable tool for implementation into electronic health records to prioritize potential FH cases for genetic confirmation

Postdiagnosis dietary factors, supplement use and breast cancer prognosis : Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis

Little is known about how diet might influence breast cancer prognosis. The current systematic reviews and meta-analyses summarise the evidence on postdiagnosis dietary factors and breast cancer outcomes from randomised controlled trials and longitudinal observational studies. PubMed and Embase were searched through 31st October 2021. Random-effects linear dose-response meta-analysis was conducted when at least three studies with sufficient information were available. The quality of the evidence was evaluated by an independent Expert Panel. We identified 108 publications. No meta-analysis was conducted for dietary patterns, vegetables, wholegrains, fish, meat, and supplements due to few studies, often with insufficient data. Meta-analysis was only possible for all-cause mortality with dairy, isoflavone, carbohydrate, dietary fibre, alcohol intake and serum 25-hydroxyvitamin D (25(OH)D), and for breast cancer-specific mortality with fruit, dairy, carbohydrate, protein, dietary fat, fibre, alcohol intake and serum 25(OH)D. The results, with few exceptions, were generally null. There was limited-suggestive evidence that predefined dietary patterns may reduce the risk of all-cause and other causes of death; that isoflavone intake reduces the risk of all-cause mortality (relative risk (RR) per 2 mg/day: 0.96, 95% confidence interval (CI): 0.92-1.02), breast cancer-specific mortality (RR for high vs low: 0.83, 95% CI: 0.64-1.07), and recurrence (RR for high vs low: 0.75, 95% CI: 0.61-0.92); that dietary fibre intake decreases all-cause mortality (RR per 10 g/day: 0.87, 95% CI: 0.80-0.94); and that serum 25(OH)D is inversely associated with all-cause and breast cancer-specific mortality (RR per 10 nmol/L: 0.93, 95% CI: 0.89-0.97 and 0.94, 95% CI: 0.90-0.99, respectively). The remaining associations were graded as limited-no conclusion

Postdiagnosis recreational physical activity and breast cancer prognosis : Global Cancer Update Programme (CUP Global) systematic literature review and meta-analysis

It is important to clarify the associations between modifiable lifestyle factors such as physical activity and breast cancer prognosis to enable the development of evidence-based survivorship recommendations. We performed a systematic review and meta-analyses to summarise the evidence on the relationship between postbreast cancer diagnosis physical activity and mortality, recurrence and second primary cancers. We searched PubMed and Embase through 31st October 2021 and included 20 observational studies and three follow-up observational analyses of patients enrolled in clinical trials. In linear dose-response meta-analysis of the observational studies, each 10-unit increase in metabolic equivalent of task (MET)-h/week higher recreational physical activity was associated with 15% and 14% lower risk of all-cause (95% confidence interval [CI]: 8%-22%, studies = 12, deaths = 3670) and breast cancer-specific mortality (95% CI: 4%-23%, studies = 11, deaths = 1632), respectively. Recreational physical activity was not associated with breast cancer recurrence (HR = 0.97, 95% CI: 0.91-1.05, studies = 6, deaths = 1705). Nonlinear dose-response meta-analyses indicated 48% lower all-cause and 38% lower breast cancer-specific mortality with increasing recreational physical activity up to 20 MET-h/week, but little further reduction in risk at higher levels. Predefined subgroup analyses across strata of body mass index, hormone receptors, adjustment for confounders, number of deaths, menopause and physical activity intensities were consistent in direction and magnitude to the main analyses. Considering the methodological limitations of the included studies, the independent Expert Panel concluded ‘limited-suggestive’ likelihood of causality for an association between recreational physical activity and lower risk of all-cause and breast cancer-specific mortality

Postdiagnosis body fatness, recreational physical activity, dietary factors and breast cancer prognosis : Global Cancer Update Programme (CUP Global) summary of evidence grading

Based on the Global Cancer Update Programme, formally known as the World Cancer Research Fund/American Institute for Cancer Research Continuous Update Project, we performed systematic reviews and meta-analyses to investigate the association of postdiagnosis body fatness, physical activity and dietary factors with breast cancer prognosis. We searched PubMed and Embase for randomised controlled trials and longitudinal observational studies from inception to 31 October 2021. We calculated summary relative risks (RRs) and 95% confidence intervals (CIs) using random-effects meta-analyses. An independent Expert Panel graded the quality of evidence according to predefined criteria. The evidence on postdiagnosis body fatness and higher all-cause mortality (RR per 5 kg/m2 in body mass index: 1.07, 95% CI: 1.05-1.10), breast cancer-specific mortality (RR: 1.10, 95% CI: 1.06-1.14) and second primary breast cancer (RR: 1.14, 95% CI: 1.04-1.26) was graded as strong (likelihood of causality: probable). The evidence for body fatness and breast cancer recurrence and other nonbreast cancer-related mortality was graded as limited (likelihood of causality: limited-suggestive). The evidence on recreational physical activity and lower risk of all-cause (RR per 10 metabolic equivalent of task-hour/week: 0.85, 95% CI: 0.78-0.92) and breast cancer-specific mortality (RR: 0.86, 95% CI: 0.77-0.96) was judged as limited-suggestive. Data on dietary factors was limited, and no conclusions could be reached except for healthy dietary patterns, isoflavone and dietary fibre intake and serum 25(OH)D concentrations that were graded with limited-suggestive evidence for lower risk of the examined outcomes. Our results encourage the development of lifestyle recommendations for breast cancer patients to avoid obesity and be physically active

An update of the WCRF/AICR systematic literature review on esophageal and gastric cancers and citrus fruits intake

Purpose: The 2007 World Cancer Research Fund/American Institute for Cancer Research expert report concluded that foods containing vitamin C probably protect against esophageal cancer and fruits probably protect against gastric cancer. Most of the previous evidence was from case–control studies, which may be affected by recall and selection biases. More recently, several cohort studies have examined these associations. We conducted a systematic literature review of prospective studies on citrus fruits intake and risk of esophageal and gastric cancers. Methods: PubMed was searched for studies published until 1 March 2016. We calculated summary relative risks and 95 % confidence intervals (95 % CI) using random-effects models. Results: With each 100 g/day increase of citrus fruits intake, a marginally significant decreased risk of esophageal cancer was observed (summary RR 0.86, 95 % CI 0.74–1.00, 1,057 cases, six studies). The associations were similar for squamous cell carcinoma (RR 0.87, 95 % CI 0.69–1.08, three studies) and esophageal adenocarcinoma (RR 0.93, 95 % CI 0.78–1.11, three studies). For gastric cancer, the nonsignificant inverse association was observed for gastric cardia cancer (RR 0.75, 95 % CI 0.55–1.01, three studies), but not for gastric non-cardia cancer (RR 1.02, 95 % CI 0.90–1.16, four studies). Consistent summary inverse associations were observed when comparing the highest with lowest intake, with statistically significant associations for esophageal (RR 0.77, 95 % CI 0.64–0.91, seven studies) and gastric cardia cancers (RR 0.62, 95 % CI 0.39–0.99, three studies). Conclusions: Citrus fruits may decrease the risk of esophageal and gastric cardia cancers, but further studies are needed