Ignite Creation Date:
2025-12-24 @ 4:17 PM
Ignite Modification Date:
2026-03-05 @ 6:47 PM
Study NCT ID:
NCT02810366
Status:
UNKNOWN
Last Update Posted:
2016-06-23
First Post:
2016-04-11
Is Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Physician Versus Computer Coding of Verbal Autopsies
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'SINGLE', 'whoMasked': ['PARTICIPANT']}, 'primaryPurpose': 'BASIC_SCIENCE', 'interventionModel': 'PARALLEL'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 12500}}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2015-09'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2016-06', 'completionDateStruct': {'date': '2016-12', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2016-06-19', 'studyFirstSubmitDate': '2016-04-11', 'studyFirstSubmitQcDate': '2016-06-19', 'lastUpdatePostDateStruct': {'date': '2016-06-23', 'type': 'ESTIMATED'}, 'studyFirstPostDateStruct': {'date': '2016-06-23', 'type': 'ESTIMATED'}, 'primaryCompletionDateStruct': {'date': '2016-09', 'type': 'ESTIMATED'}}, 'outcomesModule': {'otherOutcomes': [{'measure': 'Number of households that responded "poorly" to the short verbal autopsy questionnaire with narrative versus a long questionnaire without a narrative, as reported by the surveyor', 'timeFrame': '1 year', 'description': 'Household preference of short verbal autopsy questionnaire with narrative versus a long questionnaire without a narrative'}], 'primaryOutcomes': [{'measure': 'Equivalence (CSMF Accuracy) of cause of death distribution between physician versus computer coded verbal autopsies', 'timeFrame': '1 year', 'description': 'Use CSMF Accuracy to measure the equivalence of the cause of death distribution between the physician and computer coded VA arms of this study, in order to assess whether the performance of physician vs. computer coding of VAs are comparable at the population level'}], 'secondaryOutcomes': [{'measure': 'Equivalence of cause of death assignment at the population (CSMF Accuracy) and individual (sensitivity) levels of physician versus lay surveyor collected verbal autopsies', 'timeFrame': '1 year', 'description': 'For each of the deaths for which a VA was independently collected by a physician and a lay person, calculate the CSMF Accuracy and sensitivity of the causes of death assigned to these VAs, in order to assess if the final cause of death assigned differs when a physician versus a lay person conducts the VA data collection'}]}, 'oversightModule': {'oversightHasDmc': False}, 'conditionsModule': {'keywords': ['Verbal Autopsy', 'Physician-coded verbal autopsy', 'Computer-coded verbal autopsy', 'InterVA', 'Naive Bayes Classifier (NBC)', 'Tariff', 'InSilicoVA', 'Randomised Control Trial', 'SmartVA', 'King-Lu'], 'conditions': ['Fatal Outcome']}, 'referencesModule': {'references': [{'pmid': '24495312', 'type': 'BACKGROUND', 'citation': 'Leitao J, Desai N, Aleksandrowicz L, Byass P, Miasnikof P, Tollman S, Alam D, Lu Y, Rathi SK, Singh A, Suraweera W, Ram F, Jha P. Comparison of physician-certified verbal autopsy with computer-coded verbal autopsy for cause of death assignment in hospitalized patients in low- and middle-income countries: systematic review. BMC Med. 2014 Feb 4;12:22. doi: 10.1186/1741-7015-12-22.'}, {'pmid': '24495855', 'type': 'BACKGROUND', 'citation': 'Desai N, Aleksandrowicz L, Miasnikof P, Lu Y, Leitao J, Byass P, Tollman S, Mee P, Alam D, Rathi SK, Singh A, Kumar R, Ram F, Jha P. Performance of four computer-coded verbal autopsy methods for cause of death assignment compared with physician coding on 24,000 deaths in low- and middle-income countries. BMC Med. 2014 Feb 4;12:20. doi: 10.1186/1741-7015-12-20.'}, {'pmid': '26607695', 'type': 'BACKGROUND', 'citation': 'Miasnikof P, Giannakeas V, Gomes M, Aleksandrowicz L, Shestopaloff AY, Alam D, Tollman S, Samarikhalaj A, Jha P. Naive Bayes classifiers for verbal autopsies: comparison to physician-based classification for 21,000 child and adult deaths. BMC Med. 2015 Nov 25;13:286. doi: 10.1186/s12916-015-0521-2.'}, {'pmid': '31242925', 'type': 'DERIVED', 'citation': 'Jha P, Kumar D, Dikshit R, Budukh A, Begum R, Sati P, Kolpak P, Wen R, Raithatha SJ, Shah U, Li ZR, Aleksandrowicz L, Shah P, Piyasena K, McCormick TH, Gelband H, Clark SJ. Automated versus physician assignment of cause of death for verbal autopsies: randomized trial of 9374 deaths in 117 villages in India. BMC Med. 2019 Jun 27;17(1):116. doi: 10.1186/s12916-019-1353-2.'}]}, 'descriptionModule': {'briefSummary': 'The objective of this study is to compare the performance of computer-coded verbal autopsies (CCVA) to physician-coded verbal autopsies (PCVA) at the population level. In order to do so a randomised control trial is being conducted in five districts of India. In each district, 50% of deaths are randomly selected for PCVA and the rest for CCVA. The cause of death distribution for both groups are then compared within each district. If the performance of PCVA and CCVA are comparable, the attained distributions should be similar.', 'detailedDescription': 'BACKGROUND\n\nMost deaths in low and middle-income countries occur out of hospital and without medical attention and certification at the time of death. Hence, information on causes of death (COD) is lacking. In these settings, verbal autopsies (VAs), typically involving lay non-medical interviews of living family members or close associates of the deceased about the details of death, with subsequent assignment of COD by physician, can be used to estimate COD patterns.\n\nAlthough VA is being commonly used for acquiring community-based COD data, its application and mode of assignment of COD may vary. The choice of physician-certified verbal autopsy (PCVA) coding versus computer-coded verbal autopsy methods (CCVA) has been widely debated. Both these methods have limitations. While PCVA methods suffer from inter and intra-observer differences in coding in addition to physician time consumption and expense, the accuracy of CCVA methods which are faster and less expensive than PCVA have not been assessed in different settings. A literature search yielded only one study that have systematically assessed the performance of four computer-coded verbal autopsy methods for COD assignment compared with physician coding of VAs on 24,000 deaths in low and middle-income countries (Miasnikof et al. 2015).\n\nHere the investigators propose the first ever randomised control trial assessing PCVA versus CCVA at the population level.\n\nSTUDY DESIGN\n\nThis randomised control trial will be conducted in three states of India; a total of 12,500 deaths that occurred in the last five years will be collected via VA. In each district (five districts across the three states - see below), 50% of deaths are randomly selected for PCVA and the rest for CCVA. The COD distribution for both groups are then compared within each district. If the performance of PCVA and CCVA are comparable, the attained distributions should be similar.\n\nStudy districts in India (x number of anticipated VAs to be collected from approx. y number of households):\n\n* Amravati, Maharashtra (2500 VAs from \\~12,500 households)\n* Anand and Kheda districts, Gujarat (5000 VAs from \\~25,000 households)\n* Sangrur and Mansa districts, Punjab (5000 VAs from \\~25,000 households)\n\nOBJECTIVES\n\n* Primary Objective: To assess physician versus computer coding of VAs at the population level - Do computer algorithms perform as well as physician coding of VAs when determining the COD distribution at the population level.\n* Secondary Objective: To assess the quality of physician versus lay surveyor VA data collection - Does the quality of symptom information collected or final COD assigned differ when a physician versus a lay person carries out the VA data collection.\n* Tertiary Objective: To assess household preference of short VA questionnaire with narrative versus a long questionnaire without a narrative - Which VA instrument do households prefer.\n\nDATA COLLECTION\n\nData collection for the study will proceed in two phases.\n\n* Phase 1: Enumeration and VA (short questionnaire with narrative, and long questionnaire with narrative) by lay data collectors. VA questionnaires were designed based on World Health Organization (WHO) recommendations.\n* Phase 2: Physician re-sampling for 50% of the VAs to be used for PCVA The data will be collected using a laptop/tablet in an electronic format in the local language.\n\nQuality control/Quality Assurance:\n\n1. Random 2-5% of cases will be re-interviewed by surveyors with the Quality Control Survey\n2. An audio recording of the entire data collection will be done for quality control and monitoring.\n\nANALYSIS PLAN\n\n* Primary Objective: COD for 50% of VAs will be assigned by trained physicians using the Million Death Study (MDS) physician coding system; this includes dual, independent coding of VA records, disagreements resolved by reconciliation, and remaining cases by adjudication by a third physician. The assignment of CODs will be in line with the international classification of disease version 10 (ICD-10). The remaining 50% of deaths will be independently assigned COD by five leading CCVA algorithms. If the performance of PCVA and CCVA are comparable, the attained COD distributions at the population level should be similar, this "similarity" will be assessed by calculating the Cause Specific Mortality Fraction (CSMF) Accuracy for each algorithm\'s COD assignment in each district against the CSMF of the PCVAs in the respective district.\n* Secondary Objective: Half of the PCVAs in each district will be re-interviewed by physicians, and CODs will be assigned to these re-interviewed VAs using the MDS physician coding system described above. To assess concordance of COD assignment between lay person and physician collected VAs, the CSMF Accuracy will be calculated to determine concordance at the population level, while Sensitivity and Partial Chance Corrected Concordance (PCCC) will be calculated to assess similarity of COD assignment at the individual level.\n* Tertiary Objective: Respondents cooperation with the short VA questionnaire with narrative versus the long questionnaire without a narrative will be assessed to determine which VA instrument households prefer. A focus group with surveyors to receive their feedback on using both instruments in the field will also be conducted.\n\nThe results of this study will be presented as three separate trials (one trial per state). The results of the first trial will be used for hypothesis generation.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'minimumAge': '18 Years', 'healthyVolunteers': True, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* All deaths that have occurred in the last five years\n\nExclusion Criteria:\n\n* None'}, 'identificationModule': {'nctId': 'NCT02810366', 'briefTitle': 'Physician Versus Computer Coding of Verbal Autopsies', 'organization': {'class': 'OTHER', 'fullName': 'Centre for Global Health Research, Toronto'}, 'officialTitle': 'Physician Versus Computer Coding of Verbal Autopsies, a Randomised Control Trial', 'orgStudyIdInfo': {'id': 'PCVA vs CCVA'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'ACTIVE_COMPARATOR', 'label': 'Physician Coded Verbal Autopsy', 'description': 'Of the approximately 12,500 VAs collected, 50% in each district will be randomly collected using the "electronic Verbal Autopsy" (eVA) instrument.\n\nIn addition to "general information" about the deceased (e.g. name, sex, age, etc.), this VA instrument contains a short checklist questionnaire to capture from the respondent the signs and symptoms noted during the final illness, followed by a free-text narrative.\n\nCause of death for these VAs will be assigned by trained physicians using the MDS physician coding system; this includes dual, independent coding of VA records, disagreements resolved by reconciliation, and remaining cases by adjudication by a third physician. The assignment of cause of deaths will be in line with the international classification of disease version 10 (ICD-10).', 'interventionNames': ['Other: Physician versus Computer Coded Verbal Autopsy']}, {'type': 'EXPERIMENTAL', 'label': 'Computer Coded Verbal Autopsy', 'description': 'Of the approximately 12,500 VAs collected, 50% in each district will be randomly collected using the "Extended Symptom List" (ESL) VA instrument.\n\nIn addition to "general information" about the deceased (e.g. name, sex, age, etc.), this VA instrument contains a long checklist questionnaire to capture from the respondent the signs and symptoms noted during the final illness. This VA instrument does not contain a free-text narrative.\n\nThe cause of death for these VAs will be independently assigned by five leading computer-coding VA algorithms. The assignment of cause of deaths will be in line with 17 broad cause of death categories.', 'interventionNames': ['Other: Physician versus Computer Coded Verbal Autopsy']}], 'interventions': [{'name': 'Physician versus Computer Coded Verbal Autopsy', 'type': 'OTHER', 'otherNames': ['PCVA vs. CCVA'], 'description': 'Comparing the performance of computer coded verbal autopsies (CCVA) to physician coded verbal autopsies (PCVA) at the population level.', 'armGroupLabels': ['Computer Coded Verbal Autopsy', 'Physician Coded Verbal Autopsy']}]}, 'contactsLocationsModule': {'locations': [{'zip': '388325', 'city': 'Karamsad', 'state': 'Gujarat', 'status': 'RECRUITING', 'country': 'India', 'contacts': [{'name': 'Dinesh Kumar, MD', 'role': 'CONTACT', 'email': 'drdineshkl@charutarhealth.org'}], 'facility': 'HM Patel Center for Medical Care and Education', 'geoPoint': {'lat': 22.54243, 'lon': 72.90392}}, {'zip': '400 012', 'city': 'Mumbai', 'state': 'Maharashtra', 'status': 'RECRUITING', 'country': 'India', 'contacts': [{'name': 'Atul Budukh, MD', 'role': 'CONTACT', 'email': 'atul.budukh@gmail.com', 'phone': '+91-9920863064'}], 'facility': 'Tata Memorial Centre', 'geoPoint': {'lat': 19.07283, 'lon': 72.88261}}, {'zip': '400 088', 'city': 'Mumbai', 'state': 'Maharashtra', 'status': 'COMPLETED', 'country': 'India', 'facility': 'International Institute of Population Sciences', 'geoPoint': {'lat': 19.07283, 'lon': 72.88261}}], 'centralContacts': [{'name': 'Rehana Begum, MD', 'role': 'CONTACT', 'email': 'BegumR@smh.ca', 'phone': '+919945908671'}, {'name': 'Prabhat Jha, MD, PhD', 'role': 'CONTACT', 'email': 'prabhat.jha@utoronto.ca', 'phone': '+14168646042'}], 'overallOfficials': [{'name': 'Abhishek Singh, PhD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Associate Professor, International Institute of Population Sciences'}, {'name': 'Atul Budukh, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Assistant Professor Epidemiology, Tata Memorial Centre'}, {'name': 'Dinesh Kumar, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Associate Professor, HM Patel Center for Medical Care and Education'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'YES', 'description': 'Personal identifiers within each collected verbal autopsy will be anonymized. This anonymized dataset will be made publically available.'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'Centre for Global Health Research, Toronto', 'class': 'OTHER'}, 'collaborators': [{'name': 'International Institute for Population Sciences', 'class': 'UNKNOWN'}, {'name': 'Tata Memorial Hospital', 'class': 'OTHER_GOV'}, {'name': 'HM Patel Center for Medical Care and Education', 'class': 'UNKNOWN'}], 'responsibleParty': {'type': 'SPONSOR'}}}}