Development of a risk prediction score for hypertension incidence using Japanese health checkup data

IntroductionThe prognostic value of symptoms at disease presentation of advanced gastro-oesophageal cancer is unknown. Thus, the aim of this study was to characterise these symptoms and correlate them with the outcome, so new prognostic markers can be defined.MethodsWe analysed clinical data including symptoms, therapies and survival of patients with stage IV gastro-oesophageal cancer treated between 2002 and 2018 at the Vienna General Hospital, Austria. Initial symptoms as well as stenosis in endoscopy and HER2 positivity were evaluated in a cross-validation model to ascertain the impact of each variable on patient survival.ResultsIn total, 258 patients were evaluated. Five factors (stenosis in endoscopy, weight loss, HER2 positivity, dyspepsia, ulcer or active bleeding) have proven to be statistically relevant prognostic factors and were given a count of +1 and −1, if applicable. The resulting score ranges between −3 and +2. The survival probability for 180 days with a score of −3/–2, −1, 0, +1 and +2 is 90%, 80%, 73%, 72% and 42%, whereas for 2 years, it is 30%, 30%, 8%, 7% and 3%, respectively. The median overall survival of a score of −3/–2, −1, 0, +1 and +2 was 579 (95% CI 274 to not measurable), 481 (95% CI 358 to 637), 297 (95% CI 240 to 346), 284 (95% CI 205 to 371), 146 (95% CI 120 to 229) days, respectively.ConclusionThe data from this retrospective study indicate that the Viennese risk prediction score for Advanced Gastroesophageal carcinoma based on Alarm Symptoms score provides independent prognostic information that may support clinical decision making at diagnosis of advanced gastro-oesophageal cancer. Our findings should be evaluated in prospective studies.

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The use of spirometry testing prior to cardiac surgery may impact the Society of Thoracic Surgeons risk prediction score: A prospective study in a cohort of patients at high risk for chronic lung disease

Journal of Thoracic and Cardiovascular Surgery ◽

10.1016/j.jtcvs.2009.10.010 ◽

2010 ◽

Vol 139 (3) ◽

pp. 686-691 ◽

Cited By ~ 12

Author(s):

Niv Ad ◽

Linda Henry ◽

Linda Halpin ◽

Sharon Hunt ◽

Scott Barnett ◽

...

Keyword(s):

Cardiac Surgery ◽

High Risk ◽

Prospective Study ◽

Lung Disease ◽

Risk Prediction ◽

Chronic Lung Disease ◽

Prediction Score ◽

A Prospective Study

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A Risk Prediction Score for Kidney Failure or Mortality in Rhabdomyolysis

JAMA Internal Medicine ◽

10.1001/jamainternmed.2013.9774 ◽

2013 ◽

Vol 173 (19) ◽

pp. 1821 ◽

Cited By ~ 86

Author(s):

Gearoid M. McMahon ◽

Xiaoxi Zeng ◽

Sushrut S. Waikar

Keyword(s):

Risk Prediction ◽

Kidney Failure ◽

Prediction Score

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A novel risk prediction score in atrial fibrillation for a net clinical outcome from the ENGAGE AF-TIMI 48 randomized clinical trial

European Heart Journal ◽

10.1093/eurheartj/ehw565 ◽

2017 ◽

pp. ehw565 ◽

Cited By ~ 6

Author(s):

Christina L. Fanola ◽

Robert P. Giugliano ◽

Christian T. Ruff ◽

Marco Trevisan ◽

Francesco Nordio ◽

...

Keyword(s):

Atrial Fibrillation ◽

Clinical Trial ◽

Clinical Outcome ◽

Randomized Clinical Trial ◽

Risk Prediction ◽

Prediction Score

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Identification and Validation of a Proliferation-Associated Score Model Predicting Survival in Lung Adenocarcinomas

Disease Markers ◽

10.1155/2021/3219594 ◽

2021 ◽

Vol 2021 ◽

pp. 1-25

Author(s):

Yunyi Bian ◽

Qihai Sui ◽

Guoshu Bi ◽

Yuansheng Zheng ◽

Mengnan Zhao ◽

...

Keyword(s):

Lung Adenocarcinoma ◽

Risk Prediction ◽

Functional Enrichment ◽

Prediction Score ◽

Differentially Expressed ◽

Survival Prediction ◽

Regulation Mechanism ◽

Adenocarcinoma Cells ◽

Lung Adenocarcinoma Cells ◽

Score Model

Aim. This study is aimed at building a risk model based on the genes that significantly altered the proliferation of lung adenocarcinoma cells and exploring the underlying mechanisms. Methods. The data of 60 lung adenocarcinoma cell lines in the Cancer Dependency Map (Depmap) were used to identify the genes whose knockout led to dramatical acceleration or deacceleration of cell proliferation. Then, univariate Cox regression was performed using the survival data of 497 patients with lung adenocarcinoma in The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) model was used to construct a risk prediction score model. Patients with lung adenocarcinoma from TCGA were classified into high- or low-risk groups based on the scores. The differences in clinicopathologic, genomic, and immune characteristics between the two groups were analyzed. The prognosis of the genes in the model was verified with immunohistochemical staining in 100 samples from the Department of Thoracic Surgery, Zhongshan Hospital, and the alteration in the proliferation rate was checked after these genes were knocked down in lung adenocarcinoma cells (A549 and H358). Results. A total of 55 genes were found to be significantly related to survival by combined methods, which were crucial to tumor progression in functional enrichment analysis. A six-gene-based risk prediction score, including the proteasome subunit beta type-6 (PSMB6), the heat shock protein family A member 9 (HSPA9), the deoxyuridine triphosphatase (DUT), the cyclin-dependent kinase 7 (CDK7), the polo-like kinases 1 (PLK1), and the folate receptor beta 2 (FOLR2), was built using the LASSO method. The high-risk group classified with the score model was characterized by poor overall survival (OS), immune infiltration, and relatively higher mutation load. A total of 9864 differentially expressed genes and 138 differentially expressed miRNAs were found between the two groups. Also, a nomogram comparing score model, age, and the stage was built to predict OS for patients with lung adenocarcinoma. Using immunohistochemistry, the expression levels of PSMB6, HSPA9, DUT, CDK7, and PLK1 were found to be higher in lung adenocarcinoma tissues of patients, while the expression of FOLR2 was low, which was consistent with survival prediction. The knockdown of PSMB6 and HSPA9 by siRNA significantly downregulated the proliferation of A549 and H358 cells. Conclusion. The proposed score model may function as a promising risk prediction tool for patients with lung adenocarcinoma and provide insights into the molecular regulation mechanism of lung adenocarcinoma.

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