Clinical trial NCT05106725: Wearable Devices and Biomarkers Project (Healthiomics)
Official title: Study of Clinical Biomarkers in Human Health and Disease (Healthiomics)
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Brain Cancer
Neurological Disorder
Neurological Cancer
Keywords: wearables
digital health
biospecimens
Lead sponsor: CureScience
Sponsor class: OTHER
First posted: 2021-11-04
Enrollment: 3500
Sex: ALL
Minimum age (years): 18
Standard ages: ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: PROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Potential participants will be referred to the study by a medical provider. Participants may be of sex/gender, race, or ethnic background. Participants must have the capacity to consent, or have a legally authorized representative willing to consent.

Brief 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.

Detailed 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.

Eligibility criteria: 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.

Primary outcomes:
measure: Specimen and data storage
timeFrame: 4 years
Secondary outcomes:
measure: Specimen and data analysis
timeFrame: 4 years
measure: Collaboration
timeFrame: 4 years
Other outcomes:
Locations:
city: San Diego
country: United States
facility: CureScience Institute
state: California
Study officials:
affiliation: CureScience
name: Feng Lin, MD PhD
role: PRINCIPAL_INVESTIGATOR
References:
citation: 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.
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.
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.
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.
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.
citation: Gomez GG, Kruse CA. Mechanisms of malignant glioma immune resistance and sources of immunosuppression. Gene Ther Mol Biol. 2006;10(A):133-146.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.