Developed by Shray Alag, The Harker School
Sections: Correlations,
Clinical Trials, and HPO
Navigate: Clinical Trials and HPO
Name (Synonyms) | Correlation | |
---|---|---|
drug3892 | nasopharyngeal Covid 19 RT-PCR Wiki | 0.50 |
drug612 | COVID-19 convalescent plasma treatment Wiki | 0.50 |
drug765 | Clinical Trial Matching Wiki | 0.50 |
Name (Synonyms) | Correlation | |
---|---|---|
D002292 | Carcinoma, Renal Cell NIH | 0.71 |
D002285 | Carcinoma, Intraductal, Noninfiltrating NIH | 0.50 |
D002278 | Carcinoma in Situ NIH | 0.50 |
Name (Synonyms) | Correlation | |
---|---|---|
D016889 | Endometrial Neoplasms NIH | 0.50 |
D004938 | Esophageal Neoplasms NIH | 0.50 |
D013274 | Stomach Neoplasms NIH | 0.50 |
D012878 | Skin Neoplasms NIH | 0.50 |
D044584 | Carcinoma, Ductal NIH | 0.50 |
D018270 | Carcinoma, Ductal, Breast NIH | 0.50 |
D009423 | Nervous System Neoplasms NIH | 0.50 |
D007680 | Kidney Neoplasms NIH | 0.50 |
D016543 | Central Nervous System Neoplasms NIH | 0.50 |
D005909 | Glioblastoma NIH | 0.50 |
D008113 | Liver Neoplasms NIH | 0.50 |
D006528 | Carcinoma, Hepatocellular NIH | 0.50 |
D007822 | Laryngeal Neoplasms NIH | 0.50 |
D013736 | Testicular Neoplasms NIH | 0.50 |
D001943 | Breast Neoplasms NIH | 0.45 |
D002583 | Uterine Cervical Neoplasms NIH | 0.35 |
D012004 | Rectal Neoplasms NIH | 0.35 |
D018281 | Cholangiocarcinoma NIH | 0.35 |
D018358 | Neuroendocrine Tumors NIH | 0.35 |
D010190 | Pancreatic Neoplasms NIH | 0.29 |
D006258 | Head and Neck Neoplasms NIH | 0.29 |
D003110 | Colonic Neoplasms NIH | 0.25 |
D008175 | Lung Neoplasms NIH | 0.20 |
Name (Synonyms) | Correlation | |
---|---|---|
HP:0030731 | Carcinoma HPO | 1.00 |
HP:0005584 | Renal cell carcinoma HPO | 0.71 |
HP:0002896 | Neoplasm of the liver HPO | 0.50 |
Name (Synonyms) | Correlation | |
---|---|---|
HP:0008069 | Neoplasm of the skin HPO | 0.50 |
HP:0012114 | Endometrial carcinoma HPO | 0.50 |
HP:0100006 | Neoplasm of the central nervous system HPO | 0.50 |
HP:0010788 | Testicular neoplasm HPO | 0.50 |
HP:0009726 | Renal neoplasm HPO | 0.50 |
HP:0012174 | Glioblastoma multiforme HPO | 0.50 |
HP:0100751 | Esophageal neoplasm HPO | 0.50 |
HP:0004375 | Neoplasm of the nervous system HPO | 0.50 |
HP:0001402 | Hepatocellular carcinoma HPO | 0.50 |
HP:0006753 | Neoplasm of the stomach HPO | 0.50 |
HP:0030075 | Ductal carcinoma in situ HPO | 0.50 |
HP:0100605 | Neoplasm of the larynx HPO | 0.50 |
HP:0003002 | Breast carcinoma HPO | 0.45 |
HP:0100634 | Neuroendocrine neoplasm HPO | 0.35 |
HP:0100743 | Neoplasm of the rectum HPO | 0.35 |
HP:0030153 | Cholangiocarcinoma HPO | 0.35 |
HP:0030079 | Cervix cancer HPO | 0.35 |
HP:0002894 | Neoplasm of the pancreas HPO | 0.29 |
HP:0012288 | Neoplasm of head and neck HPO | 0.29 |
HP:0003003 | Colon cancer HPO | 0.25 |
HP:0100526 | Neoplasm of the lung HPO | 0.20 |
Navigate: Correlations HPO
There are 4 clinical trials
TRACERx Renal: This is a translational study, which, aims to develop prognostic and predictive biomarkers for patients with renal cell carcinoma (RCC). CAPTURE Sub-study: Covid-19 antiviral response in a pan-tumour immune monitoring study
Description: Outcomes will be quantified using descriptive statistics with the intention of providing hypothesis-generating data for use in future studies.
Measure: To validate ITH index and WGII as stage and grade independent prognostic markers of progression free survival in patients with ccRCC mutation in a gene of interest Time: From trial activation until trial closure approximately 1st September 2023Description: Outcomes will be quantified using descriptive statistics
Measure: CAPTURE Sub-study: Describe the population characteristics between SARS-CoV-2 positive and negative cancer patients Time: From sub-study activation until trial closure approximately 2027International registry for cancer patients evaluating the feasibility and clinical utility of an Artificial Intelligence-based precision oncology clinical trial matching tool, powered by a virtual tumor boards (VTB) program, and its clinical impact on pts with advanced cancer to facilitate clinical trial enrollment (CTE), as well as the financial impact, and potential outcomes of the intervention.
Description: CTE Accrual
Measure: Proportion of patients Eligible for CTE versus Actual CTE Time: Through study completion, an average of 1 yearDescription: OS
Measure: Impact of CTE on Overall Survival (OS), estimated by Kaplan-Meier and Cox multivariable survival analysis Time: 4 yearsDescription: PFS
Measure: Impact of CTE on Progression-Free Survival (PFS), estimated by Kaplan-Meier and Cox multivariable survival analysis Time: 4 yearsDescription: To identify barriers to accruals to clinical trials, as measured and reported by a questionnaire
Measure: Identification of Barriers to CTE Time: Through study completion, an average of 1 yearDescription: To Analyze Individual Standard of Care Chemotherapy Utilization (nominal), across treatment lines (numeric); data will be combined and aggregated to report chemotherapy utilization rate (%).
Measure: Real World Data Analytics Time: Through study completion, an average of 1 yearDescription: VTB Use Rate
Measure: Virtual Tumor Board Utilization Time: Through study completion, an average of 1 yearDescription: Time to CTE
Measure: Time from Intervention to Actual CTE (months) Time: Through study completion, an average of 1 yearThis study investigates the impact of COVID-19 pandemic on out-of-pocket costs, lost wages, and unemployment in patients with breast cancer undergoing breast surgery. Post-mastectomy reconstructive patients are at high risk for financial toxicity (adverse effects of escalating health care cost on well-being). The goal of this study is to collect information about financial costs patients may have as a result of surgical treatment for cancer with or without breast reconstruction and to learn if COVID-19 affects patient costs of breast reconstruction. This may help researchers demonstrate the financial consequences of undergoing breast surgery.
Description: Will be measured by the Comprehensive Score for financial Toxicity questionnaire. Summary statistics including mean, standard deviation, median, and range for continuous variables, and frequency count and percentage for categorical variables will be provided. Various subgroup analyses may occur. In these cases, continuous variables will be compared using the two-sample t-test and categorical variables will be compared using chi-squared test or Fisher's exact test. Multivariate regression analysis will be performed to account for confounding and to increase the robustness of any causal inference.
Measure: Prevalence of financial toxicity Time: Up to 1 year after completion of studyDescription: Summary statistics including mean, standard deviation, median, and range for continuous variables, and frequency count and percentage for categorical variables will be provided. Various subgroup analyses may occur. In these cases, continuous variables will be compared using the two sample t-test and categorical variables will be compared using chi-squared test or Fisher's exact test. Multivariate regression analysis will be performed to account for confounding and to increase the robustness of any causal inference.
Measure: Correlation between economic disruption from coronavirus disease 2019 (COVID-19) and financial toxicity Time: Up to 1 year after completion of studyDescription: Will be assessed using the Short Form-12 survey. Summary statistics including mean, standard deviation, median, and range for continuous variables, and frequency count and percentage for categorical variables will be provided. Various subgroup analyses may occur. In these cases, continuous variables will be compared using the two-sample t-test and categorical variables will be compared using chi-squared test or Fisher's exact test. Multivariate regression analysis will be performed to account for confounding and to increase the robustness of any causal inference.
Measure: Relationship between financial toxicity and patient reported quality of life Time: Up to 1 year after completion of studyDescription: Will be assessed using the Breast-Q survey. Summary statistics including mean, standard deviation, median, and range for continuous variables, and frequency count and percentage for categorical variables will be provided. Various subgroup analyses may occur. In these cases, continuous variables will be compared using the two-sample t-test and categorical variables will be compared using chi-squared test or Fisher's exact test. Multivariate regression analysis will be performed to account for confounding and to increase the robustness of any causal inference.
Measure: Relationship between financial toxicity and patient reported satisfaction with breast reconstruction Time: Up to 1 year after completion of studySince December 2019, a new disease named COVID-19 linked to a new coronavirus, SARS-CoV2 has emerged in China in the city of Wuhan, Hubei province, spreading very quickly to all 5 continents, and responsible for a pandemic. France is the third most affected country in Europe after Italy and Spain. Groups of patients at a higher risk of developing a severe form of COVID-19 have been defined: this include patients with immunosuppressive disease as cancer or patients with advanced cirrhosis of the liver. Coronavirus liver injury had been described with SARS-CoV 1 and MERS-CoV. There is no data on liver damage associated with COVID-19 infection for compensated or decompensated cirrhotic patients. The objectives of this project are to estimate the incidence of COVID-19 in hepatocellular carcinoma population, both hospital and ambulatory, and to study the impact on the frequency of severe forms, the prognosis, but also liver function, and the management of hepatocellular carcinoma, in this context of pandemic
Description: Incidence of COVID-19 infection in patients with hepatocellular carcinoma in France
Measure: Incidence of COVID-19 infection in patients with hepatocellular carcinoma in France Time: 6 monthsAlphabetical listing of all HPO terms. Navigate: Correlations Clinical Trials
Data processed on December 13, 2020.
An HTML report was created for each of the unique drugs, MeSH, and HPO terms associated with COVID-19 clinical trials. Each report contains a list of either the drug, the MeSH terms, or the HPO terms. All of the terms in a category are displayed on the left-hand side of the report to enable easy navigation, and the reports contain a list of correlated drugs, MeSH, and HPO terms. Further, all reports contain the details of the clinical trials in which the term is referenced. Every clinical trial report shows the mapped HPO and MeSH terms, which are also hyperlinked. Related HPO terms, with their associated genes, protein mutations, and SNPs are also referenced in the report.
Drug Reports MeSH Reports HPO Reports