Trial Outcomes & Findings for Validation of the Freund Clock Drawing Test to Screen for Cognitive Dysfunction in Cancer Patients (NCT NCT01749995)

NCT ID: NCT01749995

Last Updated: 2021-03-04

Results Overview

A Receiver Operating Characteristic (ROC) analysis was applied in order to validate the Freund Clock Drawing Test at its predefined cut-off of ≤ 4. This ROC analysis illustrates the capacity of the Freund Clock Drawing Test to identify elderly cancer patients in need of a more in-depth cognitive evaluation with the Folstein MMSE within comprehensive geriatric assessment. The ROC curve is a fundamental tool for diagnostic test evaluation. In a ROC curve the true positive rate (Sensitivity) is plotted in function of the false positive rate (100-Specificity) for different cut-off points of a parameter. The AUC (Area Under Curve) is the area enclosed by the ROC curve. The range of possible AUC values is \[0, 1\]. A perfect classifier has AUC = 1 and a completely random classifier has AUC = 0.5. Usually, themodel will score somewhere in between.

• Recruitment status: COMPLETED
• Target enrollment: 200 participants
• Primary outcome timeframe: Baseline
• Results posted on: 2021-03-04

Participant Flow

Participant milestones

Measure	Cohort Older patients with cancer receiving a full CGA
Overall Study STARTED	200
Overall Study COMPLETED	196
Overall Study NOT COMPLETED	4

Reasons for withdrawal

Withdrawal data not reported

Baseline Characteristics

Race and Ethnicity were not collected from any participant.

Baseline characteristics by cohort

Measure	Cohort n=196 Participants Older patients with cancer receiving a full CGA
Age, Continuous	79.0 years n=196 Participants
Sex: Female, Male Female	93 Participants n=196 Participants
Sex: Female, Male Male	103 Participants n=196 Participants
Region of Enrollment Belgium	196 participants n=196 Participants

PRIMARY outcome

Timeframe: Baseline

A Receiver Operating Characteristic (ROC) analysis was applied in order to validate the Freund Clock Drawing Test at its predefined cut-off of ≤ 4. This ROC analysis illustrates the capacity of the Freund Clock Drawing Test to identify elderly cancer patients in need of a more in-depth cognitive evaluation with the Folstein MMSE within comprehensive geriatric assessment. The ROC curve is a fundamental tool for diagnostic test evaluation. In a ROC curve the true positive rate (Sensitivity) is plotted in function of the false positive rate (100-Specificity) for different cut-off points of a parameter. The AUC (Area Under Curve) is the area enclosed by the ROC curve. The range of possible AUC values is [0, 1]. A perfect classifier has AUC = 1 and a completely random classifier has AUC = 0.5. Usually, themodel will score somewhere in between.

Outcome measures

Measure	Cohort n=196 Participants Older patients with cancer receiving a full CGA
Validation of the Freund Clock Drawing Test, and Its Predefined Cut-off of ≤ 4, as a Screening Tool to Identify Elderly Cancer Patients in Need of a More In-depth Cognitive Evaluation With the Folstein MMSE Within Comprehensive Geriatric Assessment	0.95 unitless Interval 0.78 to 1.0

PRIMARY outcome

Timeframe: Baseline

During the PROGERCAN study, a database was set up in which the results of the CGA were coupled to the data available in the Cancer Registry of the General Hospital Groeninge. In this project, we aim continue this registration.

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: Baseline

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: Baseline

Determination of the time-saving when using the Freund Clock Drawing Test instead of the Folstein MMSE

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: Baseline

Outcome measures

Outcome data not reported

SECONDARY outcome

Timeframe: Baseline

Outcome measures

Outcome data not reported

Adverse Events

Cohort

Serious events: 0 serious events

Other events: 0 other events

Deaths: 0 deaths

Serious adverse events

Adverse event data not reported

Other adverse events

Adverse event data not reported

Additional Information

Dr. Philip Debruyne

General Hospital Groeninge, Kortrijk, Belgium

Phone: +32 056 63 39 00

Email: philip.debruyne@azgroeninge.be

Results disclosure agreements

• Principal investigator is a sponsor employee
• Publication restrictions are in place