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Clinical Trial Details — Status: Recruiting

Administrative data

NCT number NCT05106725
Other study ID # CSI-01-0706
Secondary ID
Status Recruiting
Phase
First received
Last updated
Start date October 11, 2021
Est. completion date December 31, 2025

Study information

Verified date August 2023
Source CureScience
Contact Amanda Wilburn
Phone 8588002873
Email awilburn@curescience.orgg
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The purpose of this study is to collect clinical data, biological specimens (e.g., blood, tumor, cerebrospinal fluid, urine sample, etc.), and digital health data from patients with tumors, cancer and/or neurological disorders in order to perform research studies that could advance patient care. By collecting these specimens, the investigators plan to create and maintain a biorepository to make data and specimens available to collaborating investigators performing research to discover predictive biomarkers, patterns of care, and personalized treatments that could directly improve the care of our patients through focused proof-of-concept clinical trials.


Description:

For brain tumors in particular, this study will provide an important historical dataset against which to compare the addition of novel agents to standard chemoradiation. Despite advancements in surgery, radiotherapy and chemotherapy, the prognosis of malignant gliomas remains poor. Even worse is the prognosis of patients with metastatic brain tumors. However, it is recognized that a small number of brain tumor patients respond durably to specific modalities and treatment regimens and discovery of clinical, imaging, and genetic biomarkers would significantly advance the care of these patients. The development, validation, and application of prognostic biomarkers for primary and secondary brain tumors that predict patient treatment outcome and guide personalized treatment for each patient are of considerable clinical importance. Such prognostic models will allow more informed, pre-treatment decisions about patient response to specific treatments and judiciously guide stratification of patients for specific treatments and enrollment into clinical trials. Prognostic models will also provide a guide and platform for studying many other types of cancer and neurological disorders. The significance of evaluating the impact of therapy on quality of life and patient-centered outcomes is now widely acknowledged and recognized as one of several measures used to determine clinical benefit. There is increasing evidence that patient reported outcome (PRO) measures are sensitive to changes in disease and treatment characteristics. For example, more recent clinical trials for cancer are now describing the relationship between symptom-based PRO measures and traditional clinical trial endpoints (e.g., overall survival (OS) and progression free survival (PFS)). The relationships between symptoms, signs, and functions are complex, and there is a need to continue to analyze these relationships to determine what is being caused by the treatment and what is being caused by the disease. Distinguishing outcomes of normal aging from disease is also a challenge, therefore comparing results from patients without neurological disorders ("normal controls") across the spectrum will be an important component of the study.


Recruitment information / eligibility

Status Recruiting
Enrollment 3500
Est. completion date December 31, 2025
Est. primary completion date December 31, 2025
Accepts healthy volunteers Accepts Healthy Volunteers
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria: - Participant or participant's legally authorized representative has the ability to understand and the willingness to provide a signed and dated informed consent form. - Participant is = 18 years of age. - Participant had/has a scheduled appointment with oncology or neurosciences services at the participating medical and surgical facility. - Participant is characterized by at least one of the following criteria: 1. Has a neurological complication from any type of cancer, or is under evaluation for a possible cancer diagnosis or neurologic complication. Participant may be newly diagnosed, in relapse, or be free of disease at the time of recruitment. Participant without a confirmed cancer diagnosis is eligible.; OR 2. Has a neurological disorder, or is under evaluation for a possible diagnosis of a neurological disorder; OR 3. Does not meet the characteristic of either a. or b. above. This participant would be considered a "healthy control" for cancer and neurological disorders. Exclusion Criteria: - Participant or participant's legally authorized representative is unable to provide informed consent.

Study Design


Locations

Country Name City State
United States CureScience Institute San Diego California

Sponsors (1)

Lead Sponsor Collaborator
CureScience

Country where clinical trial is conducted

United States, 

References & Publications (21)

Bent B, Goldstein BA, Kibbe WA, Dunn JP. Investigating sources of inaccuracy in wearable optical heart rate sensors. NPJ Digit Med. 2020 Feb 10;3:18. doi: 10.1038/s41746-020-0226-6. eCollection 2020. — View Citation

Braun KL, Tsark JU, Powers A, Croom K, Kim R, Gachupin FC, Morris P. Cancer patient perceptions about biobanking and preferred timing of consent. Biopreserv Biobank. 2014 Apr;12(2):106-12. doi: 10.1089/bio.2013.0083. — View Citation

Chen W. Clinical applications of PET in brain tumors. J Nucl Med. 2007 Sep;48(9):1468-81. doi: 10.2967/jnumed.106.037689. Epub 2007 Aug 17. — View Citation

Fulham MJ, Bizzi A, Dietz MJ, Shih HH, Raman R, Sobering GS, Frank JA, Dwyer AJ, Alger JR, Di Chiro G. Mapping of brain tumor metabolites with proton MR spectroscopic imaging: clinical relevance. Radiology. 1992 Dec;185(3):675-86. doi: 10.1148/radiology.185.3.1438744. — View Citation

Gillinov S, Etiwy M, Wang R, Blackburn G, Phelan D, Gillinov AM, Houghtaling P, Javadikasgari H, Desai MY. Variable Accuracy of Wearable Heart Rate Monitors during Aerobic Exercise. Med Sci Sports Exerc. 2017 Aug;49(8):1697-1703. doi: 10.1249/MSS.0000000000001284. — View Citation

Gomez GG, Kruse CA. Mechanisms of malignant glioma immune resistance and sources of immunosuppression. Gene Ther Mol Biol. 2006;10(A):133-146. — View Citation

Hawighorst H, Knopp MV, Debus J, Hoffmann U, Grandy M, Griebel J, Zuna I, Essig M, Schoenberg SO, DeVries A, Brix G, van Kaick G. Pharmacokinetic MRI for assessment of malignant glioma response to stereotactic radiotherapy: initial results. J Magn Reson Imaging. 1998 Jul-Aug;8(4):783-8. doi: 10.1002/jmri.1880080406. — View Citation

Heesters MA, Kamman RL, Mooyaart EL, Go KG. Localized proton spectroscopy of inoperable brain gliomas. Response to radiation therapy. J Neurooncol. 1993 Jul;17(1):27-35. doi: 10.1007/BF01054271. — View Citation

Helfer JL, Wen PY, Blakeley J, Gilbert MR, Armstrong TS. Report of the Jumpstarting Brain Tumor Drug Development Coalition and FDA clinical trials clinical outcome assessment endpoints workshop (October 15, 2014, Bethesda MD). Neuro Oncol. 2016 Mar;18 Suppl 2(Suppl 2):ii26-ii36. doi: 10.1093/neuonc/nov270. — View Citation

Hewitt R, Watson PH, Dhir R, Aamodt R, Thomas G, Mercola D, Grizzle WE, Morente MM. Timing of consent for the research use of surgically removed tissue: is postoperative consenting acceptable? Cancer. 2009 Jan 1;115(1):4-9. doi: 10.1002/cncr.23999. No abstract available. — View Citation

Hoskin PJ, Saunders MI, Goodchild K, Powell ME, Taylor NJ, Baddeley H. Dynamic contrast enhanced magnetic resonance scanning as a predictor of response to accelerated radiotherapy for advanced head and neck cancer. Br J Radiol. 1999 Nov;72(863):1093-8. doi: 10.1259/bjr.72.863.10700827. — View Citation

Huhn SL, Mohapatra G, Bollen A, Lamborn K, Prados MD, Feuerstein BG. Chromosomal abnormalities in glioblastoma multiforme by comparative genomic hybridization: correlation with radiation treatment outcome. Clin Cancer Res. 1999 Jun;5(6):1435-43. — View Citation

Huisman TA, Schwamm LH, Schaefer PW, Koroshetz WJ, Shetty-Alva N, Ozsunar Y, Wu O, Sorensen AG. Diffusion tensor imaging as potential biomarker of white matter injury in diffuse axonal injury. AJNR Am J Neuroradiol. 2004 Mar;25(3):370-6. — View Citation

Kmiecik J, Poli A, Brons NH, Waha A, Eide GE, Enger PO, Zimmer J, Chekenya M. Elevated CD3+ and CD8+ tumor-infiltrating immune cells correlate with prolonged survival in glioblastoma patients despite integrated immunosuppressive mechanisms in the tumor microenvironment and at the systemic level. J Neuroimmunol. 2013 Nov 15;264(1-2):71-83. doi: 10.1016/j.jneuroim.2013.08.013. Epub 2013 Aug 31. — View Citation

Lin S, Yu W, Wang B, Zhao Y, En K, Zhu J, Cheng X, Zhou C, Lin H, Wang Z, Hojaiji H, Yeung C, Milla C, Davis RW, Emaminejad S. Noninvasive wearable electroactive pharmaceutical monitoring for personalized therapeutics. Proc Natl Acad Sci U S A. 2020 Aug 11;117(32):19017-19025. doi: 10.1073/pnas.2009979117. Epub 2020 Jul 27. — View Citation

Malmberg KJ, Ljunggren HG. Escape from immune- and nonimmune-mediated tumor surveillance. Semin Cancer Biol. 2006 Feb;16(1):16-31. doi: 10.1016/j.semcancer.2005.07.007. Epub 2005 Sep 2. — View Citation

Nelson BW, Allen NB. Accuracy of Consumer Wearable Heart Rate Measurement During an Ecologically Valid 24-Hour Period: Intraindividual Validation Study. JMIR Mhealth Uhealth. 2019 Mar 11;7(3):e10828. doi: 10.2196/10828. — View Citation

Prendergast CT, Anderton SM. Immune cell entry to central nervous system--current understanding and prospective therapeutic targets. Endocr Metab Immune Disord Drug Targets. 2009 Dec;9(4):315-27. doi: 10.2174/187153009789839219. — View Citation

Schmitt P, Kotas M, Tobermann A, Haase A, Flentje M. Quantitative tissue perfusion measurements in head and neck carcinoma patients before and during radiation therapy with a non-invasive MR imaging spin-labeling technique. Radiother Oncol. 2003 Apr;67(1):27-34. doi: 10.1016/s0167-8140(03)00024-0. — View Citation

Stehlik J, Schmalfuss C, Bozkurt B, Nativi-Nicolau J, Wohlfahrt P, Wegerich S, Rose K, Ray R, Schofield R, Deswal A, Sekaric J, Anand S, Richards D, Hanson H, Pipke M, Pham M. Continuous Wearable Monitoring Analytics Predict Heart Failure Hospitalization: The LINK-HF Multicenter Study. Circ Heart Fail. 2020 Mar;13(3):e006513. doi: 10.1161/CIRCHEARTFAILURE.119.006513. Epub 2020 Feb 25. — View Citation

Thomson EA, Nuss K, Comstock A, Reinwald S, Blake S, Pimentel RE, Tracy BL, Li K. Heart rate measures from the Apple Watch, Fitbit Charge HR 2, and electrocardiogram across different exercise intensities. J Sports Sci. 2019 Jun;37(12):1411-1419. doi: 10.1080/02640414.2018.1560644. Epub 2019 Jan 18. — View Citation

* Note: There are 21 references in allClick here to view all references

Outcome

Type Measure Description Time frame Safety issue
Primary Specimen and data storage To collect and store biological specimens (such as, but not limited to, tissue, blood, urine, cerebrospinal fluid, etc.), data from functional and anatomical imaging modalities, digital health data and clinical data from patients with cancer or neurological disorders, those who are under evaluation for a possible cancer or neurologic disorders, or healthy controls. 4 years
Secondary Specimen and data analysis To perform multi-modality analysis of specimens for biomarker discovery. 4 years
Secondary Collaboration To make specimens and data available to collaborating investigators performing IRB-approved research of cancer or neurological disorders. 4 years
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