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If a data manager generated no additional manual queries on data in an EDC system and the data were deemed clean, why could the data appear to be not clean during the next review?
A. The medical monitor can override safety information entered in the system.
B. The study coordinator can change the data due to re-review of the source.
C. The data manager may have accidentally changed the data.
D. The CRA can change the data during a quality review of source to database.
Answer: B
Explanation:
In an Electronic Data Capture (EDC) system, even after a data manager completes all manual queries and marks data as "clean," the data may later appear unclean if the site (study coordinator) makes subsequent updates in the system after re-reviewing the source documents.
According to the Good Clinical Data Management Practices (GCDMP, Chapter: Electronic Data Capture Systems), site users maintain the authority to modify data entries as long as the system remains open for data entry. The EDC system audit trail captures such changes, which can automatically invalidate prior data reviews, triggering new discrepancies or changing system edit-check statuses.
This situation commonly occurs when the site identifies corrections in the source (e.g., wrong date or lab result) and updates the EDC form accordingly. These post-cleaning changes require additional review cycles to ensure the database reflects accurate and verified information before final lock.
Options B, C, and D are incorrect - CRAs and medical monitors cannot directly change EDC data; they can only raise queries or request updates.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Electronic Data Capture Systems, Section 6.3 - Post-Cleaning Data Changes and Audit Trails ICH E6 (R2) GCP, Section 5.5.3 - Data Integrity and Change Control FDA 21 CFR Part 11 - Electronic Records: Change Documentation Requirements
NEW QUESTION # 21
A Data Manager is importing data from an external facility. Which is commonly checked first?
A. Data in the incoming files are internally consistent
B. Incoming files have the expected number of records
C. Incoming files are conformant to the data transfer specifications
D. Data in incoming files are consistent with existing data in the study database
Answer: C
Explanation:
When importing external data (e.g., laboratory or imaging results) into a clinical database, the first step in data import quality control is to verify that incoming files conform to the pre-specified data transfer specifications (DTS).
According to the GCDMP (Chapter: External Data Transfers and Integration), the Data Transfer Specification defines file structure, variable names, data types, delimiters, record counts, and validation rules. The initial import check confirms that the received file matches the technical and structural requirements before content or record consistency is evaluated.
Subsequent checks-such as record counts (A), data consistency with existing database (C), and internal logical consistency (D)-are performed only after the file structure is validated and confirmed to match the specifications. Failure to perform this first check may cause import errors or corrupted data loads.
Thus, the first and most critical verification step is ensuring file conformity to the agreed data transfer specifications, making option B correct.
Reference (CCDM-Verified Sources):
SCDM GCDMP, Chapter: External Data Transfers, Section 4.2 - Data Transfer File Validation and Import Checks ICH E6(R2) GCP, Section 5.5.3 - Validation of Computerized Systems and Data Imports
NEW QUESTION # 22
Which information should an auditee expect prior to an audit?
A. Standard operating procedures
B. Audit plan or agenda
C. Corrective action requests
D. Auditor's credentials and certification number
Answer: B
Explanation:
Prior to an audit, the auditee should expect to receive an audit plan or agenda, which outlines the scope, objectives, schedule, and logistics of the audit.
According to the GCDMP (Chapter: Quality Assurance and Audits), an audit plan ensures transparency, preparation, and efficient execution. It typically includes details such as:
The audit scope and objectives,
The audit team members,
Documents or processes to be reviewed, and
The audit schedule and timeframe.
This allows the auditee to prepare the necessary records, staff, and facilities. While the auditor's credentials (option A) may be shared informally, they are not a regulatory requirement. Corrective actions (option B) are outcomes of the audit, not pre-audit materials. Standard Operating Procedures (option C) may be requested during the audit but are not provided in advance.
Thus, Option D - Audit Plan or Agenda - is the correct and compliant answer.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Quality Assurance and Audits, Section 6.1 - Pre-Audit Planning and Communication ICH E6 (R2) Good Clinical Practice, Section 5.19.3 - Audit Procedures and Responsibilities FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations - Section 8.1 - Audit Preparation and Planning
NEW QUESTION # 23
If database auditing is used for data quality control during a study, which is the optimal timing of the audits?
A. After the first few cases have been entered
B. Immediately following database lock
C. Periodically throughout the study
D. A week or two before database lock
Answer: C
Explanation:
Database audits are conducted to ensure ongoing data accuracy, completeness, and compliance throughout the lifecycle of a clinical trial. According to the Good Clinical Data Management Practices (GCDMP, Chapter: Data Quality Assurance and Control), quality audits are most effective when performed periodically during study conduct, rather than waiting until study completion.
Performing audits periodically allows early detection of data entry errors, protocol deviations, and system inconsistencies, thereby reducing the risk of large-scale data issues before database lock. This proactive approach aligns with risk-based quality management principles outlined in ICH E6(R2) and ensures corrective actions are implemented in real time.
Options A and B represent reactive quality control, which occurs too late to prevent data issues. Option C (after first few cases) provides initial validation but does not ensure continuous oversight.
Therefore, option D - "Periodically throughout the study" - represents the optimal and compliant timing for quality audits of the database.
Reference (CCDM-Verified Sources):
SCDM GCDMP, Chapter: Data Quality Assurance and Control, Section 5.3 - Ongoing Quality Control and Auditing ICH E6(R2) GCP, Section 5.1.1 - Quality Management System and Risk-Based Monitoring FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6.5 - Data Review and Auditing Practices
NEW QUESTION # 24
During a database audit, it was determined that there were more errors than expected. Who is responsible for assessing the overall impact on the analysis of the data?
A. Statistician
B. Data Manager
C. Quality Auditor
D. Investigator
Answer: A
Explanation:
The Statistician is responsible for assessing the overall impact of data errors on the analysis and study results.
According to the Good Clinical Data Management Practices (GCDMP, Chapter: Data Quality Assurance and Control) and ICH E9 (Statistical Principles for Clinical Trials), while the Data Manager ensures data accuracy and completeness through cleaning and validation, the Statistician determines whether the observed data discrepancies are statistically significant or if they may affect the validity, power, or interpretability of the study's outcomes.
The Quality Auditor (C) identifies and reports issues but does not quantify analytical impact. The Investigator (D) is responsible for clinical oversight, not statistical assessment. Thus, after a database audit, the Statistician (B) performs a formal evaluation to determine whether the magnitude and nature of the errors could bias results or require reanalysis.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Data Quality Assurance and Control, Section 7.3 - Data Audit and Impact Assessment ICH E9 - Statistical Principles for Clinical Trials, Section 3.2 - Data Quality and Analysis Impact Assessment FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations - Data Validation and Analysis Review
NEW QUESTION # 25
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