Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D008175', 'term': 'Lung Neoplasms'}, {'id': 'D013274', 'term': 'Stomach Neoplasms'}, {'id': 'D008113', 'term': 'Liver Neoplasms'}, {'id': 'D015179', 'term': 'Colorectal Neoplasms'}, {'id': 'D010190', 'term': 'Pancreatic Neoplasms'}, {'id': 'D004938', 'term': 'Esophageal Neoplasms'}, {'id': 'D001943', 'term': 'Breast Neoplasms'}, {'id': 'D002583', 'term': 'Uterine Cervical Neoplasms'}, {'id': 'D010051', 'term': 'Ovarian Neoplasms'}, {'id': 'D016889', 'term': 'Endometrial Neoplasms'}, {'id': 'D001749', 'term': 'Urinary Bladder Neoplasms'}, {'id': 'D011471', 'term': 'Prostatic Neoplasms'}, {'id': 'D018281', 'term': 'Cholangiocarcinoma'}], 'ancestors': [{'id': 'D012142', 'term': 'Respiratory Tract Neoplasms'}, {'id': 'D013899', 'term': 'Thoracic Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D008171', 'term': 'Lung Diseases'}, {'id': 'D012140', 'term': 'Respiratory Tract Diseases'}, {'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D013272', 'term': 'Stomach Diseases'}, {'id': 'D008107', 'term': 'Liver Diseases'}, {'id': 'D007414', 'term': 'Intestinal Neoplasms'}, {'id': 'D003108', 'term': 'Colonic Diseases'}, {'id': 'D007410', 'term': 'Intestinal Diseases'}, {'id': 'D012002', 'term': 'Rectal Diseases'}, {'id': 'D004701', 'term': 'Endocrine Gland Neoplasms'}, {'id': 'D010182', 'term': 'Pancreatic Diseases'}, {'id': 'D004700', 'term': 'Endocrine System Diseases'}, {'id': 'D006258', 'term': 'Head and Neck Neoplasms'}, {'id': 'D004935', 'term': 'Esophageal Diseases'}, {'id': 'D001941', 'term': 'Breast Diseases'}, {'id': 'D012871', 'term': 'Skin Diseases'}, {'id': 'D017437', 'term': 'Skin and Connective Tissue Diseases'}, {'id': 'D014594', 'term': 'Uterine Neoplasms'}, {'id': 'D005833', 'term': 'Genital Neoplasms, Female'}, {'id': 'D014565', 'term': 'Urogenital Neoplasms'}, {'id': 'D002577', 'term': 'Uterine Cervical Diseases'}, {'id': 'D014591', 'term': 'Uterine Diseases'}, {'id': 'D005831', 'term': 'Genital Diseases, Female'}, {'id': 'D052776', 'term': 'Female Urogenital Diseases'}, {'id': 'D005261', 'term': 'Female Urogenital Diseases and Pregnancy Complications'}, {'id': 'D000091642', 'term': 'Urogenital Diseases'}, {'id': 'D000091662', 'term': 'Genital Diseases'}, {'id': 'D010049', 'term': 'Ovarian Diseases'}, {'id': 'D000291', 'term': 'Adnexal Diseases'}, {'id': 'D006058', 'term': 'Gonadal Disorders'}, {'id': 'D014571', 'term': 'Urologic Neoplasms'}, {'id': 'D001745', 'term': 'Urinary Bladder Diseases'}, {'id': 'D014570', 'term': 'Urologic Diseases'}, {'id': 'D052801', 'term': 'Male Urogenital Diseases'}, {'id': 'D005834', 'term': 'Genital Neoplasms, Male'}, {'id': 'D005832', 'term': 'Genital Diseases, Male'}, {'id': 'D011469', 'term': 'Prostatic Diseases'}, {'id': 'D000230', 'term': 'Adenocarcinoma'}, {'id': 'D002277', 'term': 'Carcinoma'}, {'id': 'D009375', 'term': 'Neoplasms, Glandular and Epithelial'}, {'id': 'D009370', 'term': 'Neoplasms by Histologic Type'}]}}, 'protocolSection': {'designModule': {'bioSpec': {'retention': 'SAMPLES_WITH_DNA', 'description': 'Tissue and blood samples'}, 'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'CASE_CONTROL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 5350}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'RECRUITING', 'startDateStruct': {'date': '2024-07-20', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-05', 'completionDateStruct': {'date': '2025-02-28', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2025-02-19', 'studyFirstSubmitDate': '2024-05-28', 'studyFirstSubmitQcDate': '2024-05-28', 'lastUpdatePostDateStruct': {'date': '2025-02-21', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-06-03', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-02-28', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'The AUC, sensitivity, specificity and tissue origin accuracy of the multi-cancer early detection model in detecting cancer or non-cancer', 'timeFrame': '12 months'}], 'secondaryOutcomes': [{'measure': 'The performance of the multi-cancer early detection model in early stage cancer and precancerous lesion cases', 'timeFrame': '12 months'}, {'measure': 'The performance of the multi-cancer early detection model in different subgroups (such as age, gender, cancer pathological classification, and clinical stage)', 'timeFrame': '12 months'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Lung Cancer', 'Gastric Cancer', 'Liver Cancer', 'Colorectal Cancer', 'Pancreatic Cancer', 'Esophageal Cancer', 'Breast Cancer', 'Cervical Cancer', 'Ovarian Cancer', 'Endometrial Cancer', 'Bladder Cancer', 'Prostate Cancer', 'Cholangiocarcinoma']}, 'descriptionModule': {'briefSummary': 'This research constitutes a multi-centric, case-control designed investigation aimed at developing and implementing a blinded validation of a machine learning-powered, multi-cancer early detection model. This is to be achieved through the prospective collection of blood specimens from newly diagnosed cancer patients and individuals devoid of a confirmed cancer diagnosis', 'detailedDescription': "Cancerous tissues, their adjacent non-cancerous tissues, along with white blood cells (WBCs) and normal tissue samples will be utilized to identify potential methylation candidate markers and investigate variations in methylation patterns among patients diagnosed with distinct cancer types. Building upon previous research and current study, a comprehensive methylation signature panel tailored specifically to cancer patients will be established.\n\nWe will prospectively collect blood samples from newly diagnosed cancer patients and non-cancer individuals to analyze and identify specific cancer signals via the detection of cfDNA methylation patterns. Following a rigorous and comprehensive research framework, a machine learning-driven model will be developed and validated through blinded testing in an independent cohort. The study aims to enroll approximately 2,650 cancer patients, with a focus on including early-stage cases to enhance the model's sensitivity in detecting cancers with favorable prognoses. Furthermore, around 2,400 control subjects, matched with cancer patients by age and gender and screened negative for cancer through routine tests, will participate as healthy or benign-condition volunteers in model development. Lastly, samples from an additional 300 patients with other tumors will be gathered to conduct interference testing, ensuring the robustness of the model's performance."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '75 Years', 'minimumAge': '40 Years', 'samplingMethod': 'NON_PROBABILITY_SAMPLE', 'studyPopulation': 'A consenting professional will invite participants, including cancer patients and healthy controls, from the main center and affiliated hospitals, to take part in a comprehensive case-control study.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria for Case Arm Participants:\n\n* 40-75 years old\n* Clinically and/or pathologically diagnosed cancer\n* No prior or undergoing any systemic or local antitumor therapy, including but not limited to surgical resection, radiochemotherapy, endocrinotherapy, targeted therapy, immunotherapy, interventional therapy, etc.\n* Able to provide a written informed consent and willing to comply with all part of the protocol procedures\n\nExclusion Criteria for Case Arm Participants:\n\n* Pregnancy or lactating women\n* Known prior or current diagnosis of other types of malignancies comorbidities\n* Have participated in an "interventional" clinical trial within the past 30 days and have taken the experimental drug;\n* Recipients of organ transplant or prior bone marrow transplant or stem cell transplant\n* Recipients of blood transfusion within 30 days prior to screen\n* Recipients of therapy in past 14 days prior to screen, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamide, hydrazine, arsenic trioxide\n* Failure to collect blood on time according to plan\n* The blood sample does not meet the requirements\n\nInclusion Criteria for Control Arm Participants:\n\n* 40-75 years old\n* Without confirmed cancer diagnosis\n* Able to provide a written informed consent and willing to comply with all part of the protocol procedures\n\nExclusion Criteria for Control Arm Participants:\n\n* Pregnancy or lactating women\n* No previous history of malignancy in other sites\n* Recipients of organ transplant or prior bone marrow transplant or stem cell transplant\n* Recipients of blood transfusion within 30 days prior to screen\n* Recipients of therapy in the past 14 days prior to screen, including oral or IV antibiotics, glucocorticoid, azacitidine, decitabine, procainamide, hydrazine, arsenic trioxide\n* Unsuitable for this trial determined by the researchers'}, 'identificationModule': {'nctId': 'NCT06440018', 'acronym': 'INSPIRE', 'briefTitle': 'INSPIRE: a Multi-Cancer Early Detection Study', 'organization': {'class': 'INDUSTRY', 'fullName': 'Singlera Genomics Inc.'}, 'officialTitle': 'INSPIRE: Integrating Circulating DNA Methylation and Fragmentomics to Scan and Pinpoint Cancer Signals Effectively', 'orgStudyIdInfo': {'id': 'multiple'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Case arm', 'description': 'Participants newly diagnosed with cancer, belonging to one of thirteen distinct cancer types.'}, {'label': 'Control arm', 'description': 'Healthy or benign condition participants with no cancer diagnosis subsequent to routine cancer screening tests.'}]}, 'contactsLocationsModule': {'locations': [{'zip': '200433', 'city': 'Shanghai', 'state': 'Shnaghai', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Chen Suo, PhD', 'role': 'CONTACT', 'email': 'suochen@fudan.edu.cn', 'phone': '86-21-54237625'}], 'facility': 'Fudan University', 'geoPoint': {'lat': 31.22222, 'lon': 121.45806}}], 'centralContacts': [{'name': 'Zhixi Su, PHD', 'role': 'CONTACT', 'email': 'zhixi.su@singlera.com', 'phone': '+862180113170', 'phoneExt': '1022'}, {'name': 'Rui Liu', 'role': 'CONTACT', 'email': 'rliu@singlera.com', 'phone': '+862180113170', 'phoneExt': '1027'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Singlera Genomics Inc.', 'class': 'INDUSTRY'}, 'collaborators': [{'name': 'Fudan University', 'class': 'OTHER'}, {'name': 'Hubei Cancer Hospital, Huazhong University of Science and Technology', 'class': 'UNKNOWN'}, {'name': 'China-Japan Friendship Hospital', 'class': 'OTHER'}, {'name': 'Shanxi Provincial Cancer Hospital', 'class': 'UNKNOWN'}, {'name': 'Xuhui Central Hospital, Fudan University', 'class': 'UNKNOWN'}, {'name': 'Shanghai Electric Power Hospital', 'class': 'UNKNOWN'}, {'name': 'East Hospital, Tongji University', 'class': 'UNKNOWN'}, {'name': "The First Affiliated Hospital of Xi' an Jiaotong University", 'class': 'UNKNOWN'}, {'name': "GaoZhou People's Hosipital", 'class': 'UNKNOWN'}, {'name': 'Anhui Provincial Hospital', 'class': 'OTHER_GOV'}, {'name': 'Beijing Friendship Hospital', 'class': 'OTHER'}], 'responsibleParty': {'type': 'SPONSOR'}}}}