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NCT ID: NCT04202874 Active, not recruiting - Clinical trials for Surgical Procedure, Unspecified

A Trial Comparing Surgeon-administered TAP Block With Placebo After Midline Laparotomy in Gynecologic Oncology

Start date: October 1, 2020
Phase: Phase 3
Study type: Interventional

Multimodal opioid-sparing analgesia is recommended in order to prevent post-operative complications and shorten length of stay. Administration by the surgeon of local anesthetics in the abdominal wall after surgery for a suspected gynaecological malignancy will be studied. Eighty women above the age of 18 and undergoing a midline laparotomy for a suspected gynecologic malignancy will be recruited. Half of these women will received a Transversus Abdominis Plane (TAP) block using local anesthetics, and half will receive a placebo (saline water). The primary outcome studied will be the total dose of opioid in morphine equivalents received in the postoperative period. The primary hypothesis is that surgeon-performed TAP blocks reduce the need for opioids after surgery. Secondary outcomes including postoperative pain scores, postoperative nausea and vomiting rates, time to flatus, incidence of clinical ileus and time to discharge from hospital will also be recorded.

NCT ID: NCT04201262 Active, not recruiting - Clinical trials for Neuromyelitis Optica

An Efficacy and Safety Study of Ravulizumab in Adult Participants With NMOSD

Start date: December 13, 2019
Phase: Phase 3
Study type: Interventional

The primary purpose of this study is to evaluate the efficacy and safety of ravulizumab for the treatment of adult participants with NMOSD.

NCT ID: NCT04201093 Active, not recruiting - Parkinson Disease Clinical Trials

Fixed-Dose Trial in Early Parkinson's Disease (PD)

TEMPO-1
Start date: December 13, 2019
Phase: Phase 3
Study type: Interventional

The purpose of this study is to evaluate the clinical efficacy, safety and pharmacokinetics (PK) of 2 fixed doses of tavapadon and placebo in participants with early PD.

NCT ID: NCT04199104 Active, not recruiting - Clinical trials for Head and Neck Squamous Cell Carcinoma

A Study of Pembrolizumab (MK-3475) With or Without Lenvatinib (E7080/MK-7902) as First Line (1L) Intervention in a Programmed Cell Death-ligand 1 (PD-L1) Selected Population With Recurrent or Metastatic Head and Neck Squamous Cell Carcinoma (R/M HNSCC) (LEAP-010) (MK-7902-010)

LEAP-10
Start date: February 5, 2020
Phase: Phase 3
Study type: Interventional

This is a study of pembrolizumab (MK-3475) with or without lenvatinib (E7080/MK-7902) as a first line intervention in a PD-L1 selected population with participants with recurrent or metastatic head and neck squamous cell carcinoma. Hypotheses include: - Pembrolizumab + lenvatinib is superior to pembrolizumab + placebo with respect to Objective Response Rate (ORR) per Response Evaluation Criteria in Solid Tumors Version 1.1 (RECIST 1.1) by blinded independent central review (BICR). - Pembrolizumab + lenvatinib is superior to pembrolizumab + placebo with respect to Progression Free Survival (PFS) per RECIST 1.1 as assessed by BICR. - Pembrolizumab + lenvatinib is superior to pembrolizumab + placebo with respect to overall survival (OS).

NCT ID: NCT04197141 Active, not recruiting - Prostate Cancer Clinical Trials

Hypofractionated Whole-Pelvis Radiotherapy (WPRT) vs Conventionally-Fractionated WPRT in Prostate Cancer

HOPE
Start date: February 7, 2020
Phase: Phase 2
Study type: Interventional

The purpose of this research study is to determine if 5 (five) fractions of external radiotherapy with higher radiation doses per fraction to the pelvis leads to similar results to the standard of care external radiotherapy treatment that is comprised of 25 fractions of external radiotherapy with lower radiation doses per fraction to the pelvis. This study aims to investigate the impact in quality of life associated with hypofractionated Whole Pelvis Radiotherapy (WPRT) in comparison to conventionally-fractionated WPRT in patients with unfavorable-intermediate and high-risk prostate cancers. This information is valuable as hypofractionated WPRT is a more attractive and convenient treatment approach, and may become the new standard of care if proven to be well-tolerated and effective. Therefore, this study aims to provide a more rational justification for use of hypofractionated WPRT in future larger randomized trials by comparing this strategy with the current standard of care. This study will also provide an initial understanding of the toxicity profile and cancer control associated with hypofractionated WPRT and High Dose Rate Brachytherapy (HDR-BT).

NCT ID: NCT04195750 Active, not recruiting - Clinical trials for Carcinoma, Renal Cell

A Study of Belzutifan (MK-6482) Versus Everolimus in Participants With Advanced Renal Cell Carcinoma (MK-6482-005)

Start date: February 27, 2020
Phase: Phase 3
Study type: Interventional

The primary objective of this study is to compare belzutifan to everolimus with respect to progression-free survival (PFS) per Response Evaluation Criteria in Solid Tumors Version 1.1 (RECIST 1.1) as assessed by Blinded Independent Central Review (BICR) and to compare everolimus with respect to overall survival (OS). The hypothesis is that belzutifan is superior to everolimus with respect to PFS and OS.

NCT ID: NCT04195568 Active, not recruiting - Clinical trials for Aneurysm, Intracranial

Evaluation of Safety and Effectiveness of Stryker Surpass Evolve™ Flow Diverter System

EVOLVE
Start date: July 7, 2020
Phase: N/A
Study type: Interventional

The primary objective of this study is to evaluate the safety and effectiveness of the Surpass™ Evolve Flow Diverter System in the treatment of unruptured, wide-neck intracranial aneurysms measuring ≤ 12 mm and located on the ICA or its branches

NCT ID: NCT04195399 Active, not recruiting - Clinical trials for Desmoid Fibromatosis

A Study of a New Drug, Nirogacestat, for Treating Desmoid Tumors That Cannot be Removed by Surgery

Start date: October 7, 2020
Phase: Phase 2
Study type: Interventional

This phase II trial studies the side effects and how well nirogacestat works in treating patients less than 18 years of age with desmoid tumors that has grown after at least one form of treatment by mouth or in the vein that cannot be removed by surgery. Nirogacestat may stop the growth of tumor cells by blocking some of the enzymes needed for cell growth.

NCT ID: NCT04194944 Active, not recruiting - Clinical trials for Non-Small Cell Lung Cancer

A Study of Selpercatinib (LY3527723) in Participants With Advanced or Metastatic RET Fusion-Positive Non-Small Cell Lung Cancer

LIBRETTO-431
Start date: February 17, 2020
Phase: Phase 3
Study type: Interventional

The reason for this study is to see if the study drug selpercatinib compared to a standard treatment is effective and safe in participants with rearranged during transfection (RET) fusion-positive non-squamous non-small cell lung cancer (NSCLC) that has spread to other parts of the body. Participants who are assigned to the standard treatment and discontinue due to progressive disease have the option to potentially crossover to selpercatinib.

NCT ID: NCT04192175 Active, not recruiting - Machine Learning Clinical Trials

Identification of Patients Admitted With COPD Exacerbations and Predicting Readmission Risk Using Machine Learning

Start date: June 1, 2019
Phase:
Study type: Observational

Patients with Chronic Obstructive Pulmonary Disease (COPD) who are admitted to hospital are at high risk of readmission. While therapies have improved and there are evidence-based guidelines to reduce readmissions, there are significant challenges to implementation including 1) identifying all patients with COPD early in admission to ensure evidence-based, high value care is provided and 2) identifying those who are at high risk of readmission in order to effectively target resources. Using machine learning and natural language processing, we want to develop models to 1) identify all patients with COPD exacerbations admitted to hospital and 2) stratify them to distinguish those who are at high risk of readmission b) How will you undertake your work? From Toronto hospitals, we will develop a very large dataset of patient admissions for all medical conditions including exacerbations of COPD from the electronic health record. This data will include both structured data such as age, gender, medications, laboratory values, co-morbidities as well as unstructured data such as discharge summaries and physician notes. Using the dataset, we will train a model through natural language processing and machine learning to be able to identify people admitted with COPD exacerbation and identify those patients who will be at high risk of readmission within 30 days. We will test the ability of these models to determine our predictive accuracies. We will then test these models at other institutions.