Age of uptake of early cancer detection facilities by low-risk and high-risk patients with familial breast and ovarian cancer

BackgroundOvarian cancer (OC) has the highest mortality rate among gynecologic malignancy. Hypoxia is a driver of the malignant progression in OC, which results in poor prognosis. We herein aimed to develop a validated model that was based on the hypoxia genes to systematically evaluate its prognosis in tumor immune microenvironment (TIM).ResultsWe identified 395 hypoxia-immune genes using weighted gene co-expression network analysis (WGCNA). We then established a nine hypoxia-related genes risk model using least absolute shrinkage and selection operator (LASSO) Cox regression, which efficiently distinguished high-risk patients from low-risk ones. We found that high-risk patients were significantly related to poor prognosis. The high-risk group showed unique immunosuppressive microenvironment, lower antigen presentation, and higher levels of inhibitory cytokines. There were also significant differences in somatic copy number alterations (SCNAs) and mutations between the high- and low-risk groups, indicating immune escape in the high-risk group. Tumor immune dysfunction and exclusion (TIDE) and SubMap algorithms showed that low-risk patients are significantly responsive to programmed cell death protein-1 (PD-1) inhibitors.ConclusionsIn this study, we highlighted the clinical significance of hypoxia in OC and established a hypoxia-related model for predicting prognosis and providing potential immunotherapy strategies.

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Screening of CHEK2 and TP53 p.R337H germ-line mutations in high-risk patients for hereditary breast and ovarian cancer from northeast of Brazil.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.1539 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. 1539-1539

Author(s):

Ivana Lucia Oliveira Nascimento ◽

Gabriela Espirito Santo Felix ◽

Taisa Manuela Bonfim Machado-Lopes ◽

Thais Bomfim ◽

Maura Romeo ◽

...

Keyword(s):

Breast Cancer ◽

Ovarian Cancer ◽

High Risk ◽

Cellular Response ◽

Germ Line ◽

Susceptibility Genes ◽

Breast And Ovarian Cancer ◽

High Risk Patients ◽

High Penetrance ◽

Risk Patients

1539 Background: CHEK2 is a molecular messenger that interacts with a checkpoint network of other susceptibility genes like ATM, BRCA1, TP53, MDM2, Cdc25A and Cdc25C. The mission of these checkpoints is to preserve the genome integrity during the cell division by regulating the cellular response to DNA damages. The TP53 p.R337H germline mutation was studied in patients with Li-Fraumeni Syndrome, breast cancer and Choroid plexus carcinomas in Southern of Brazil, but never in the Northeast. In the hereditary breast cancer the mutation frequencies of susceptibility genes of low penetrance like CHEK2 is 1-10%, while for genes of high penetrance as TP53 is <1%. Thus, the aim of this study was to screening for CHEK2 and TP53 most common germline mutations in high-risk patients for hereditary breast and ovarian cancer (HBOC) from Northeast of Brazil. Methods: It was analyzed 100 high-risk patients for HBOC from Bahia, Brazil. The genomic DNA was extract from peripheral blood. The CHEK2 mutations, c.1100delC, c.444+1G>A and p.I157T, and TP53 p.R337H mutation were genotyped by Allelic Specific-PCR or PCR-RFLP. Results: Most of the subjects had only breast cancer (86.0%), followed by ovarian (7.0%) and both breast and ovarian cancer (7.0%). Among the breast cancer cases the most common histological type was the ductal (71.0%), while among the ovarian cancer cases were the serous (57.14%). The mean age at diagnostic was 42 yrs (± 9.99). Any of the patient presented c.1100delC, c.444+1G>A and p.I157T mutations. But, two have the p.R337H mutation. Conclusions: Though there is the hypothesis that mutations of low penetrance genes, such as CHEK2, are more likely to be found than high penetrance genes, such as TP53, here it was demonstrate that three of most predisposing variants of CHEK2, c.1100delC, c.444+1G>A and p.I157T, do not have major contribution in HBOC in the population studied. While, the p.R337H, though presented in low frequency compared with the Southern of Brazil (Ashton-Prolla et al., 2012), seems to have a significant contribution in HBOC.

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Dynamic risk stratification in low-risk vs high-risk patients

Endocrine Abstracts ◽

10.1530/endoabs.49.s19.3 ◽

2017 ◽

Author(s):

Miguel Melo

Keyword(s):

High Risk ◽

Risk Stratification ◽

Low Risk ◽

High Risk Patients ◽

Dynamic Risk ◽

Risk Patients

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Faculty Opinions recommendation of Contemporary real-world outcomes of surgical aortic valve replacement in 141,905 low-risk, intermediate-risk, and high-risk patients.

Faculty Opinions – Post-Publication Peer Review of the Biomedical Literature ◽

10.3410/f.725256596.793523901 ◽

2016 ◽

Author(s):

Nawwar Al-Attar

Keyword(s):

High Risk ◽

Aortic Valve ◽

Aortic Valve Replacement ◽

Valve Replacement ◽

Real World ◽

Low Risk ◽

Intermediate Risk ◽

Surgical Aortic Valve Replacement ◽

High Risk Patients ◽

Risk Patients

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Accuracy of upper endoscopies with random biopsies to identify patients with gastric premalignant lesions who can safely be exempt from surveillance

Gastric Cancer ◽

10.1007/s10120-020-01149-2 ◽

2021 ◽

Vol 24 (3) ◽

pp. 680-690

Author(s):

Michiel C. Mommersteeg ◽

Stella A. V. Nieuwenburg ◽

Wouter J. den Hollander ◽

Lisanne Holster ◽

Caroline M. den Hoed ◽

...

Keyword(s):

Gastric Cancer ◽

High Risk ◽

Low Risk ◽

Premalignant Lesions ◽

High Risk Patients ◽

European Guidelines ◽

Progression Of Disease ◽

Risk Patients ◽

Progression Risk

Abstract Introduction Guidelines recommend endoscopy with biopsies to stratify patients with gastric premalignant lesions (GPL) to high and low progression risk. High-risk patients are recommended to undergo surveillance. We aimed to assess the accuracy of guideline recommendations to identify low-risk patients, who can safely be discharged from surveillance. Methods This study includes patients with GPL. Patients underwent at least two endoscopies with an interval of 1–6 years. Patients were defined ‘low risk’ if they fulfilled requirements for discharge, and ‘high risk’ if they fulfilled requirements for surveillance, according to European guidelines (MAPS-2012, updated MAPS-2019, BSG). Patients defined ‘low risk’ with progression of disease during follow-up (FU) were considered ‘misclassified’ as low risk. Results 334 patients (median age 60 years IQR11; 48.7% male) were included and followed for a median of 48 months. At baseline, 181/334 (54%) patients were defined low risk. Of these, 32.6% were ‘misclassified’, showing progression of disease during FU. If MAPS-2019 were followed, 169/334 (51%) patients were defined low risk, of which 32.5% were ‘misclassified’. If BSG were followed, 174/334 (51%) patients were defined low risk, of which 32.2% were ‘misclassified’. Seven patients developed gastric cancer (GC) or dysplasia, four patients were ‘misclassified’ based on MAPS-2012 and three on MAPS-2019 and BSG. By performing one additional endoscopy 72.9% (95% CI 62.4–83.3) of high-risk patients and all patients who developed GC or dysplasia were identified. Conclusion One-third of patients that would have been discharged from GC surveillance, appeared to be ‘misclassified’ as low risk. One additional endoscopy will reduce this risk by 70%.

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A Novel Epigenetic Machine Learning Model to Define Risk of Progression for Hepatocellular Carcinoma Patients

International Journal of Molecular Sciences ◽

10.3390/ijms22031075 ◽

2021 ◽

Vol 22 (3) ◽

pp. 1075

Author(s):

Luca Bedon ◽

Michele Dal Bo ◽

Monica Mossenta ◽

Davide Busato ◽

Giuseppe Toffoli ◽

...

Keyword(s):

Machine Learning ◽

Hepatocellular Carcinoma ◽

High Risk ◽

Progression Free Survival ◽

Low Risk ◽

Functional Enrichment ◽

Free Survival ◽

High Risk Patients ◽

Risk Of Progression ◽

Risk Patients

Although extensive advancements have been made in treatment against hepatocellular carcinoma (HCC), the prognosis of HCC patients remains unsatisfied. It is now clearly established that extensive epigenetic changes act as a driver in human tumors. This study exploits HCC epigenetic deregulation to define a novel prognostic model for monitoring the progression of HCC. We analyzed the genome-wide DNA methylation profile of 374 primary tumor specimens using the Illumina 450 K array data from The Cancer Genome Atlas. We initially used a novel combination of Machine Learning algorithms (Recursive Features Selection, Boruta) to capture early tumor progression features. The subsets of probes obtained were used to train and validate Random Forest models to predict a Progression Free Survival greater or less than 6 months. The model based on 34 epigenetic probes showed the best performance, scoring 0.80 accuracy and 0.51 Matthews Correlation Coefficient on testset. Then, we generated and validated a progression signature based on 4 methylation probes capable of stratifying HCC patients at high and low risk of progression. Survival analysis showed that high risk patients are characterized by a poorer progression free survival compared to low risk patients. Moreover, decision curve analysis confirmed the strength of this predictive tool over conventional clinical parameters. Functional enrichment analysis highlighted that high risk patients differentiated themselves by the upregulation of proliferative pathways. Ultimately, we propose the oncogenic MCM2 gene as a methylation-driven gene of which the representative epigenetic markers could serve both as predictive and prognostic markers. Briefly, our work provides several potential HCC progression epigenetic biomarkers as well as a new signature that may enhance patients surveillance and advances in personalized treatment.

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Does socioeconomic status make a difference? A register-based study on the extent to which cardiovascular screening in patients with inflammatory arthritis leads to recommended follow-up in general practice

RMD Open ◽

10.1136/rmdopen-2019-000940 ◽

2020 ◽

Vol 6 (2) ◽

pp. e000940

Author(s):

Anette Hvenegaard Kjeldgaard ◽

Kim Hørslev-Petersen ◽

Sonja Wehberg ◽

Jens Soendergaard ◽

Jette Primdahl

Keyword(s):

Blood Pressure ◽

Socioeconomic Status ◽

High Risk ◽

Secondary Care ◽

Inflammatory Arthritis ◽

Low Risk ◽

Risk Screening ◽

High Risk Patients ◽

Eular Recommendations ◽

Risk Patients

ObjectiveTo investigate to what extent patients with inflammatory arthritis (IA) follow recommendations given in a secondary care nurse-led cardiovascular (CV) risk screening consultation to consult their general practitioner (GP) to reduce their CV risk and whether their socioeconomic status (SES) affects adherence.MethodsAdults with IA who had participated in a secondary care screening consultation from July 2012 to July 2015, based on the EULAR recommendations, were identified. Patients were considered to have high CV risk if they had risk Systematic COronary Risk Evaluation (SCORE) ≥5%, according to the European SCORE model or systolic blood pressure ≥145 mmHg, total cholesterol ≥8 mmol/L, LDL cholesterol ≥5 mmol/L, HbA1c ≥42 mmol/mol or fasting glucose ≥6 mmol/L. The primary outcome was a consultation with their GP and at least one action focusing on CV risk factors within 6 weeks after the screening consultation.ResultsThe study comprised 1265 patients, aged 18–85 years. Of these, 336/447 (75%) of the high-risk patients and 580/819 (71%) of the low-risk patients had a GP consultation. 127/336 (38%) of high-risk patients and 160/580 (28%) of low-risk patients received relevant actions related to their CV risk, for example, blood pressure home measurement or prescription for statins, antihypertensives or antidiabetics. Education ≥10 years increased the odds for non-adherence (OR 0.58, 95% CI 0.0.37 to 0.92, p=0.02).Conclusions75% of the high-risk patients consulted their GP after the secondary care CV risk screening, and 38% of these received an action relevant for their CV risk. Higher education decreased adherence.

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Changes in patient activation following cardiac rehabilitation using the Active+me digital healthcare platform during the COVID-19 pandemic: a cohort evaluation

BMC Health Services Research ◽

10.1186/s12913-021-07363-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Gabbi Frith ◽

Kathryn Carver ◽

Sarah Curry ◽

Alan Darby ◽

Anna Sydes ◽

...

Keyword(s):

Blood Pressure ◽

High Risk ◽

Cardiac Rehabilitation ◽

Group Analysis ◽

Patient Activation ◽

Low Risk ◽

Smart Device ◽

Face To Face ◽

High Risk Patients ◽

Risk Patients

Abstract Background Restrictions on face-to-face contact, due to COVID-19, led to a rapid adoption of technology to remotely deliver cardiac rehabilitation (CR). Some technologies, including Active+me, were used without knowing their benefits. We assessed changes in patient activation measure (PAM) in patients participating in routine CR, using Active+me. We also investigated changes in PAM among low, moderate, and high risk patients, changes in cardiovascular risk factors, and explored patient and healthcare professional experiences of using Active+me. Methods Patients received standard CR education and an exercise prescription. Active+me was used to monitor patient health, progress towards goals, and provide additional lifestyle support. Patients accessed Active+me through a smart-device application which synchronised to telemetry enabled scales, blood pressure monitors, pulse oximeter, and activity trackers. Changes in PAM score following CR were calculated. Sub-group analysis was conducted on patients at high, moderate, and low risk of exercise induced cardiovascular events. Qualitative interviews explored the acceptability of Active+me. Results Forty-six patients were recruited (Age: 60.4 ± 10.9 years; BMI: 27.9 ± 5.0 kg.m2; 78.3% male). PAM scores increased from 65.5 (range: 51.0 to 100.0) to 70.2 (range: 40.7 to 100.0; P = 0.039). PAM scores of high risk patients increased from 61.9 (range: 53.0 to 91.0) to 75.0 (range: 58.1 to 100.0; P = 0.044). The PAM scores of moderate and low risk patients did not change. Resting systolic blood pressure decreased from 125 mmHg (95% CI: 120 to 130 mmHg) to 119 mmHg (95% CI: 115 to 122 mmHg; P = 0.023) and waist circumference measurements decreased from 92.8 cm (95% CI: 82.6 to 102.9 cm) to 85.3 cm (95% CI 79.1 to 96.2 cm; P = 0.026). Self-reported physical activity levels increased from 1557.5 MET-minutes (range: 245.0 to 5355.0 MET-minutes) to 3363.2 MET-minutes (range: 105.0 to 12,360.0 MET-minutes; P < 0.001). Active+me was acceptable to patients and healthcare professionals. Conclusion Participation in standard CR, with Active+me, is associated with increased patient skill, knowledge, and confidence to manage their condition. Active+me may be an appropriate platform to support CR delivery when patients cannot be seen face-to-face. Trial registration As this was not a clinical trial, the study was not registered in a trial registry.

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