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SCDM Certified Clinical Data Manager Sample Questions (Q68-Q73):

NEW QUESTION # 68
All range and logic checks have been resolved in a study. An auditor found discrepancies between the database and the source. Which reason is most likely?

Answer: D

Explanation:
Even when all range and logic checks are successfully resolved, discrepancies may still exist between the clinical database and the source documents. This typically indicates an error in data abstraction or transcription, meaning that data were incorrectly entered or extracted from the source records during the data entry or verification process.
According to the Good Clinical Data Management Practices (GCDMP, Chapter on Data Validation and Cleaning), data validation rules such as range and logic checks are designed to identify inconsistencies, missing data, or out-of-range values within the database itself. However, they do not verify the accuracy of data entry against the original source documents - that responsibility falls under source data verification (SDV), typically conducted by clinical monitors or auditors.
When an auditor detects discrepancies between source and database values after all edit checks have passed, the most probable explanation is that data were not transcribed correctly from the source, rather than a failure in programmed edit checks. This could occur due to human error during manual data entry, misinterpretation of the source document, or oversight during SDV.
Option C (Data were changed after checks were run) might occur in rare cases but would normally be documented in an audit trail per 21 CFR Part 11 and ICH E6 (R2) standards. Option B misinterprets the issue, since "logical and in range" values can still be incorrect relative to the source. Option A (Auditor error) is possible but statistically less likely, as source data verification follows strict, documented audit procedures.
Therefore, the most likely reason for such discrepancies is Option D: Data were not abstracted correctly from the source, emphasizing the importance of robust data entry training, dual data entry, and verification procedures.
Reference (CCDM-Verified Sources):
Society for Clinical Data Management (SCDM), Good Clinical Data Management Practices (GCDMP), Chapter: Data Validation and Cleaning, Section 6.5 - Source Data Verification and Reconciliation ICH E6 (R2) Good Clinical Practice, Section 5.18 - Monitoring and Source Data Verification FDA Guidance for Industry: Computerized Systems Used in Clinical Investigations, Section 6 - Source Data Accuracy and Audit Trails
21 CFR Part 11 - Electronic Records and Electronic Signatures, Subpart B: Audit Trails and Record Accuracy


NEW QUESTION # 69
ACME Intervention Co. is testing a new carotid artery stent in patients with coronary artery disease, in hopes of proving superiority over the current standard of care. After a subject signs consent, the surgeon enrolls the patient and retrieves information on which stent to use, but the surgeon does not share this information with the subject. Yesterday, the surgeon was instructed to use the control stent. Today, the surgeon has completed two surgeries: the first one the surgeon was instructed to use the control stent; the second one the surgeon was instructed to use the test stent. In what type of trial is the surgeon participating?

Answer: B

Explanation:
This scenario describes a single-blind trial, in which only one party-typically the subject-is unaware of the treatment assignment, while the investigator or surgeon knows which intervention is being administered.
In this case, the surgeon receives instructions on which stent (test or control) to use, meaning they are aware of treatment allocation. However, the subject is blinded to which device is being implanted. This setup minimizes subject bias while maintaining procedural safety since the surgeon must know which product to use.
Double-blind (A): Neither subject nor investigator knows the treatment.
Open-label (B): Both subject and investigator know the treatment.
Cross-over (D): Each subject receives both treatments in different periods.
Thus, the correct answer is C. Single-blind, as only the participant remains blinded in this surgical device trial design.
Reference (CCDM-Verified Sources):
SCDM GCDMP, Chapter: Clinical Trial Phases and Protocols, Section 3.2 - Study Blinding and Randomization Concepts ICH E6(R2) GCP, Section 1.10 - Definition of Blinding/Masking FDA Guidance for Industry: Design Considerations for Pivotal Clinical Investigations for Medical Devices, Section 5.3 - Blinding in Device Studies


NEW QUESTION # 70
In the EDC database, which factors are considered when defining user roles?

Answer: B

Explanation:
In Electronic Data Capture (EDC) systems, user roles are defined based on the functions and permissions required for specific study tasks. The most fundamental and universally applicable roles are Data Entry (performed by site staff) and Data Review (performed by monitors or data managers).
According to the GCDMP (Chapter: Technology and Electronic Data Capture Systems), defining user roles involves:
Assigning functional access levels (e.g., entry, review, query resolution).
Ensuring role-based security to protect data integrity.
Complying with 21 CFR Part 11 and ICH E6(R2) access control standards.
Options B, C, and D include functions (protocol review, analysis programming) not directly controlled within an EDC system.
Thus, option A (Data Entry and Data Review) correctly represents the two core factors considered when defining user roles.
Reference (CCDM-Verified Sources):
SCDM GCDMP, Chapter: Technology and Electronic Data Capture Systems, Section 4.3 - User Access, Roles, and Permissions ICH E6(R2) GCP, Section 5.5.3 - System Access and Security Controls FDA 21 CFR Part 11 - Access Control and Audit Trail Requirements


NEW QUESTION # 71
A Data Manager is designing a CRF for a study for which the efficacy data are not covered by the current SDTM domains. Which of the following should the Data Manager consult first?

Answer: A

Explanation:
When efficacy data are not covered by existing CDISC SDTM domains, the first resource the Data Manager should consult is the CDISC Therapeutic Area Implementation Guide (TAIG) for that therapeutic field.
According to the GCDMP (Chapter: Standards and Data Mapping), CDISC's Therapeutic Area User Guides (TAUGs) and Implementation Guides provide standardized data structures, variable definitions, controlled terminology, and implementation examples for specific diseases or therapeutic areas. These guides ensure consistency across studies, promote interoperability, and align data collection with regulatory submission expectations.
Consulting other sponsors' forms or external registries (options A and C) can be informative but do not provide authoritative CDISC-compliant standards. SNOMED terms (option B) address medical terminology, not structural data domain definitions.
Therefore, Option D is correct-CDISC TA Implementation Guides are the recognized primary reference when extending or designing SDTM-compliant CRFs.
Reference (CCDM-Verified Sources):
SCDM Good Clinical Data Management Practices (GCDMP), Chapter: Standards and Data Mapping, Section 4.2 - Use of CDISC Standards CDISC Therapeutic Area User Guides (TAUGs) - Implementation Guidance for Domain Extension FDA Data Standards Catalog - CDISC Therapeutic Area Standards


NEW QUESTION # 72
Which Clinical Study Report section would be most useful for a Data Manager to review?

Answer: A

Explanation:
The section of the Clinical Study Report (CSR) that is most useful for a Data Manager is the one that includes the enumeration and explanation of data errors. This section provides a summary of the data quality control findings, including error rates, missing data summaries, and any issues identified during data review, validation, or database lock.
According to the GCDMP (Chapter: Data Quality Assurance and Control), post-study reviews of data errors and quality findings are essential for evaluating process performance, identifying recurring issues, and informing continuous improvement in future studies.
Other sections, such as clinical narratives (A) or statistical methods (C), are outside the core scope of data management responsibilities. The data error enumeration section directly reflects the quality and integrity of the data management process and is therefore the most relevant for review.
Reference (CCDM-Verified Sources):
SCDM GCDMP, Chapter: Data Quality Assurance and Control, Section 6.4 - Quality Reporting and Error Analysis ICH E3 - Structure and Content of Clinical Study Reports, Section 14.3 - Data Quality Evaluation


NEW QUESTION # 73
......

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