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 Table of Contents  
STUDY PROTOCOL
Year : 2016  |  Volume : 1  |  Issue : 3  |  Page : 121-126

Benefit of carbohydrate deficient transferrin in detecting chronic alcohol abuse in the elderly: study protocol for a multicentre, non-randomized, open-label study


Geriatrics Department, Groupe Hospitalier Regional Mulhouse Sud Alsace, Mulhouse, France

Date of Web Publication13-Oct-2016

Correspondence Address:
Cécile Schnell
Geriatrics Department, Groupe Hospitalier Regional Mulhouse Sud Alsace, Mulhouse
France
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/2468-5658.191354

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  Abstract 

Background: Alcohol misuse affects about five million people in France. Self-reported alcohol consumption, questionnaires, biological markers like gamma-glutamyltranspeptidase (GGT), mean corpuscular volume (MCV) and carbohydrate deficient transferrin (CDT) are usually used to detect alcohol abuse. As a biological marker of alcohol misuse, the specificity of the CDT is known to be superior to GGT and MCV as well. The elderly may suffer from this pathology, but its clinical and biological detection and management are often difficult, due to a frequent denial of the alcoholism and multiple chronic diseases.
Methods/Design: A prospective, multicentre, non-randomized, open-label will be performed in the Geriatrics Department of the Hospital of Mulhouse, Alsace and in an Alsatian health care network. Inclusion criteria are: age ≥ 60 years, patients hospitalized for 1 day or 1 week in the Geriatrics department or new patients of the health care network, presence of a suitable relative or helper. A total of 200 enrolled patients are expected. Alcohol consumption will be detected by the Alcohol Use Disorder Identification Test - Consumption questionnaire. This questionnaire will be submitted to the patient and to a relative. If one of the two scores ≥ 1, a CDT analysis may be performed. Primary outcome is the benefit of CDT in the detection of chronic alcohol abuse in the elderly as compared with usual clinical detection tools. Secondary outcomes are sensitivity and specificity of disturbance of GGT and MCV in case of alcohol consumption and identification of socio-economic characteristics of alcohol abusers (socio-professional category, education level, way of life and environment).
Discussion: Findings of this trial will probably show low sensitivity and specificity of CDT to detect chronic alcohol misuse in the elderly. Those results suggest that biological markers are not more effective than questionnaires and medical interview to detect alcohol abuse, even if the consumption is initially denied. If confirmed, the results should improve medical screening, diagnosis and care in case of alcohol abuse in the elderly and reduce costs of biological analysis.
Trial registration: ClinicalTrials.gov identifier: NCT02822911, registered on 30 June 2016.
Ethics: The Committee for the Protection of Persons located in Strasbourg, France, delivered a favourable opinion on the study project.
Informed consent: The physician or the health network's care coordinator informs the patient about the study protocol and obtains the patient's assent. The investigator completes a non-opposition file and a copy is given to the patient and to his/her relative or helper.

Keywords: clinical trial; elderly; alcohol abuse; carbohydrate deficient transferring; biological detection


How to cite this article:
Schnell C. Benefit of carbohydrate deficient transferrin in detecting chronic alcohol abuse in the elderly: study protocol for a multicentre, non-randomized, open-label study. Clin Trials Degener Dis 2016;1:121-6

How to cite this URL:
Schnell C. Benefit of carbohydrate deficient transferrin in detecting chronic alcohol abuse in the elderly: study protocol for a multicentre, non-randomized, open-label study. Clin Trials Degener Dis [serial online] 2016 [cited 2019 Apr 21];1:121-6. Available from: http://www.clinicaltdd.com/text.asp?2016/1/3/121/191354


  Background Top


Alcohol misuse affects about five million people, almost ten percent of the population, in France. To date, there is no reliable prevalence rate of alcoholism in the elderly in France.

The World Health Organization (WHO) recommends drinking less than three servings of alcohol (10 g of alcohol in one serving) per day for men (21 servings/week) and less than two servings per day for women (14 servings/week). The WHO identifies three types of alcohol misuse: hazardous use (20-40 g per day for women and 40-60 g per day for men), harmful use (> 40 g/d for women and > 60 g/d for men) and alcohol addiction (World Health Organization, 2007).

Excessive alcohol consumption is frequent in the elderly but also a denied subject, by patients, families and even physicians. Prevalence of alcohol addiction is estimated at 19% in the 65-74 years old group and at 15% among those aged 75 to 85 (French Alcohol Society, 2013). This denial induces a lack of adapted medical care for this specific population (Paille, 2014). Nevertheless, there are numerous effects of chronic alcohol abuse by the elderly, including gait disturbances, falls, cognitive impairment, dementia, mental confusion, undernutrition, anxiety, clinical depression, lack of autonomy, high care costs, entry into a retirement home, which are real public health issues (American Geriatrics Society, 2003; Culberson, 2006a, b).

Self-reported alcohol consumption, questionnaires, analysis of biological markers like gamma-glutamyltranspeptidase (GGT), mean corpuscular volume (MCV) and carbohydrate deficient transferrin (CDT) are usually used to detect alcohol abuse (Mundle et al., 1999; Schwan et al., 2004; Hannuksela et al., 2007; Bearer et al., 2010; Gough et al., 2015).

Several questionnaires are able to detect alcohol abuse: CAGE (Cut off, Annoyed, Guilty, Eye opener), AUDIT (Alcohol Use Disorder Identification Test), MAST (Michigan Alcoholism Screening Test) and its short version SMAST. The AUDIT and its short version AUDIT-C are routinely used and are validated methods to detect alcohol abuse in France, including for the elderly. In men, a score of four is considered positive, three in women. A score ≥ 10 suggests alcohol addiction (Hermansson et al., 2000; Paille, 2014; French Alcohol Society, 2015).

GGT and MCV are not specific to alcohol consumption because other diseases (liver cirrhosis, blood diseases, etc.) may increase their blood levels. In usual care, CDT analysis is not systematic. Several physicians use CDT analysis in the case of high alcohol consumption suspicion, denied consumption or non-contributory results of the usual biological markers and. The specificity of the CDT is known to be superior to the GGT and MCV in detecting alcohol abuse, with a specificity of 82%, but a sensitivity of 30 to 70% (Golka and Wiese, 2004; Koch et al., 2004; Kintz et al., 2009; Fagan et al., 2014). Hepatic or pancreatic diseases, pregnancy or drugs (Salaspuro, 1999; Bråthen et al., 2000; Fleming et al., 2004) do not influence CDT results. A positive result is considered when %CDT > 1.7 (Allen et al., 1994; Schellenberg et al., 2005; Bortolotti et al., 2006). However, this superiority has not been studied in the elderly yet [Table 1]. Indeed, when it comes to elderly, most of the knowledge about alcoholism is based on research of younger populations.

Objective

This study aims to assess the benefit of the CDT to detect chronic alcohol use in the elderly, compared to usual clinical (AUDIT-C questionnaire) tools.


  Methods/Design Top


Study design

A prospective, multicenter, open-label trial will be performed at:

- The two short-term hospitalization departments named "day hospital" and "week hospital" of the Geriatrics Department of Mulhouse, GHRMSA (Groupe Hospitalier Regional Mulhouse Sud Alsace), Haut-Rhin, Alsace, France.

- The General Practitioner Support Association of Alsace, France (translated in French as the "RAG": Reseau d'Appui aux Generalistes), an Alsatian care network whose role is supervising the elderly at home and coordinating medical and nursing care.

The study is designed to evaluate the benefit of CDT in detecting alcohol abuse in the elderly. The short version of the Alcohol Use Disorder Identification Test questionnaire (AUDIT-C), known as a validated method to detect alcohol consumption in the elderly in usual medical care, is considered as the reference to estimate alcohol consumption in the study.

At the day and week hospitals: on the day of admission, a physician will define the alcohol consumption by submitting the short version of the AUDIT questionnaire: AUDIT-C to patients [Table 2]. A questionnaire will also be submitted to a patient's relative or helper, to avoid a wrong estimation of alcohol consumption by the patient. If a disagreement between the two scores is observed, such as one of the two scores equals zero whereas the other one is ≥ 1, the higher score is retained.

Characteristics of the patient's environment, lifestyle, socio-professional category and education level will be sought.

Within 3 days after enrollment, the determination of blood CDT levels will be performed for those patients with a score of at least one of the two AUDIT-C questionnaires ≥ 1.

The determination of blood GGT and MCV levels will be added to usual blood analysis in the department for each new recruited patient. If the score equals zero, no CDT determination will be performed [Figure 1].

The CDT determination will be sent to and performed by a clinical laboratory (CERBA) located in Saint-Ouen, Seine-Saint-Denis, France. The results will be returned to the physician by post mail.

In the RAG: a care coordinator will submit the AUDIT-C questionnaire to the patient and to his/her relative or helper. The CDT determination will also be performed at the CERBA laboratory within 3 days after enrollment, meanwhile blood levels of GGT and MCV will also be determined as usual analysis.

Sample size

The study expects around 200 enrolled patients.

Study participants

- Patients hospitalized in the day and week hospitals of the Geriatrics Department of Mulhouse for the first time

- Patients living in the Territory IV of Alsace (cities and surroundings of Mulhouse, Thann and Saint-Louis) who join the RAG for the first time

Inclusion criteria

Patients presenting with any of the following conditions will be considered for inclusion:

  • Patients hospitalized for one or more days in the Geriatrics Department of Mulhouse, coming from home and enrolled in the study within 48 hours after admission to GHRMSA and study procedures performed within 72 hours after admission to GHRMSA
  • New members of the RAG, living in the territory IV of Alsace, living at home and joining the RAG between 1 March and 31 October 2016 and study procedures performed within 72 hours after enrollment
  • Relative or helper available who would see the patient at home at least once a week
  • Absence of alcoholic excipient in any concomitant medication
  • Age ≥ 60 years, of either sex


Exclusion criteria

Patients presenting with any of the following conditions will be excluded from the trial:

  • Patients admitted in the Geriatrics Department of Mulhouse after more than 24 hours after admission to GHRMSA
  • Presence of any following symptoms:
    • Hepatobiliary deficiency related to a primitive biliary cirrhosis, autoimmune or viral cirrhosis
    • Hepatocellular carcinoma
    • Congenital metabolic disorder in protein glycosylation
  • Known genetics variance in B or D transferrin
  • People living in an elderly care institution
  • Age < 60 years


Withdrawal criteria

Patients will be withdrawn from the trial because of any of the following conditions:

  • Refusal to continue to participate during the trial
  • Impossibility for the clinical laboratory to perform CDT analysis.


Recruitment

A information sheet was posted in the hospital departments and also given by physicians and RAG's care coordinator to the patients and to their relatives. After providing informed non-opposition to the study, all potential participants will be screened according to the inclusion and exclusion criteria stated above.

Outcome measures

Primary outcome measure


  • Benefit of CDT in detecting chronic alcohol abuse in the elderly compared to usual clinical detection tools. The analysis will be performed within three days after enrollment when there is at least one point in the AUDIT-C questionnaire, confirming presence of alcohol consumption. A positive result is considered when %CDT > 1.7.


Secondary outcome measures



  • Sensitivity and specificity of the disturbance of GGT in case of alcohol consumption, with at least 1 point in the AUDIT-C questionnaire.
  • Sensitivity and specificity of the disturbance of MCV in case of alcohol consumption, with at least 1 point in the AUDIT-C questionnaire.
  • Socio-economic characteristics of alcohol abusers:
    • socio-professional category, based on the classification of professions and socio-professional categories of the French National institute of Statistics and economics (nine types of working classes)
    • education level, based on six levels of education type, from no degree or ninth grade. Classification created by the French National institute of Statistics and economics
    • patient's way of life and environment:

      - married or not

      - living alone or not

      - professional help provided at home by either a nurse or cleaning lady or meal delivery or senior helper


The schedule for outcome assessment is listed in [Table 3].

Data management

Data collection


A case report will be created for each included patient in HTML formatting with text field entries. This case report contains two files:

- A file containing all data obtained during the medical examination as well as the AUDIT-C score, patient environment, lifestyle, socio-professional category, education level.

- A biological file containing the CDT, GGT and MCV determination results, when appropriate.

During patient enrollment, the physician or RAG's care coordinator registers the following data in a data entry form: first name, last name, date of birth. This entry form creates a 40-hexadecimal-characters hash, which becomes the patient's unique identifier, whereas the patient's name and date of birth totally disappear from the files. The two files (data and biology) can only be completed after this hash operation. A double entry of identity characteristics confirms the data validity, providing total anonymity and avoiding re-identification. When receiving biological results, the investigator repeats the hash operation and the two files are matched with their identification number. The files are not registrable on a computer. There is no possibility to find afterwards a link between the patient's identity and the identification number.

The collected data are therefore anonymous, in conformity with the Data Protection Act number 78-17 dated 6 January 1978.

The investigator will store the completed case reports for 15 years. The study sponsor will keep the study documentation in his archives.

Data processing

Data collecting is based on the creation of a database and input masks, in conformity with the protocol and the current legislation. The study sponsor has approved the database structure and the input screens.

Unpaired data and patient's data with missing helper questionnaires will be excluded from the analysis.

Statistical analysis

All data will be analyzing using IBM SPSS Statistics ® software. Continuous variables will be expressed as headcount, mean, standard deviation, quartiles and extremes. Qualitative variables will be described as headcount and percentage.

Determination results of CDT and AUDIT-C questionnaire will be described as headcount, average, standard deviation, quartiles and extremes. The Spearman's rank-order correlation coefficient will be used to compare the correlation between these two variables.

The Student's t-test will be used to compare a quantitative variable and a dichotomous qualitative variable, in case of data homoscedasticity (equality of variances' F-test) and data adequacy to normal distribution (Shapiro-Wilk test).

A one-way analysis of variance (ANOVA) will be used to compare quantitative variable and a polytomic qualitative variable, in case of data homoscedasticity (Brown-Forsythe test) and data adequacy to normal distribution (Shapiro-Wilk test).

The chi-squared test will be used to compare qualitative variables.

In all the statistical analysis, a P value < 0.05 will be considered statistically significant.

Ethical issues

On 9 March 2016, the Committee for the protection of persons (CPP Est-IV) located in Strasbourg, Alsace, France, delivered a favourable opinion on the study project. The physician or the RAG's care coordinator informs the patient about the study protocol and obtains the patient's assent. The investigator completes a non-opposition file; a copy is given to the patient, another to his relative or helper and another one is kept in the medical file.

According to the French Public Health Policy Act 2004-806, dated 9 August 2004, any substantial changes request should be sent to the CPP for information or authorization. If so, the study protocol should be reviewed and updated.


  Trial Status Top


The study begins on 1 March 2016 and will end on 31 October 2016. Recruitment of patients is ongoing at the time of submission.


  Discussions Top


GGT and MCV are known to have low sensitivity and specificity to detect alcohol abuse. Even though CDT analysis is known to be a more specific indicator of alcohol abuse than GGT and MCV, an increased value is usually observed for high alcohol consumption, at least 50 to 80 g of alcohol drunk per day. Hazardous alcohol use is considered an AUDIT-C score ≥ 4 for men and ≥ 3 for women. Following actual knowledge, CDT seems to increase when AUDIT-C is ≥ 5 points. Although CDT is probably not a good biological marker for detecting hazardous alcohol use, it may be a more efficient marker for detecting alcohol harmful use and dependence.

This trial will try to establish the benefit of CDT analysis in the elderly and it is probable that the results will show a lack of sufficient relevance of CDT compared to clinical examination, questionnaires and declared alcohol consumption in the elderly. This trial is actually the one where the benefit of CDT is studied in the elderly. However, the results should be confirmed by other studies, with larger samples. Furthermore, our study has been carried with hospitalized patients and patients of a health care network, but those patients are not totally representative of the elderly. Future studies should explore alcohol consumption in healthy, non hospitalized aged people.

Clinical and biological diagnosis of alcohol abuse in the elderly is difficult to establish. Indeed, denial is a recurrent problem for the screening of alcohol abuse. In our study, CDT analysis has only been performed in case of AUDIT-C score ≥ 1, while an analysis for each patient could have been expected, regardless of the score. The CDT analysis was only done in case of positive score because it has been estimated that the helper's questionnaire score should make it possible to avoid patient's denial. Future studies could focus on CDT values whatever the questionnaires' scores are.

Nevertheless, when asked, it appears that many people answer sincerely about alcohol consumption.

If confirmed, our results could lead to change clinical usual care, by reducing the number and costs of biological analysis, making the clinical detection of alcoholism easier, and encouraging physicians to initiate the discussion about alcohol with their patients. [24]

 
  References Top

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Allen J, Litten R, Anton R, Cross G (1994) Carbohydrate-deficient transferrin as a measure of immoderate drinking: Remaining issues. Alcohol Clin Exp Res 18:799-812.  Back to cited text no. 1
    
2.
American Geriatrics Society (2003) Clinical guidelines for alcohol use disorders in older adults. New York: AGS.  Back to cited text no. 2
    
3.
Anton RF, Lieber C, Tabakoff B (2002) Carbohydrate-deficient transferrin and gamma-glutamyltransferase for the detection and monitoring of alcohol use: results from a multisite study. Alcohol Clin Exp Res 26:1215-1222.  Back to cited text no. 3
    
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Bearer CF, Bailey SM, Hoek JB (2010) Advancing alcohol biomarkers research. Alcohol Clin Exp Res 34:941-945.  Back to cited text no. 4
    
5.
Bortolotti F, De Paoli G, Tagliaro F (2006) Carbohydrate-deficient transferrin (CDT) as a marker of alcohol abuse: a critical review of the litterature 2001-2005. J Chromatogr B Analyt Technol Biomed Life Sci 841:96-109.  Back to cited text no. 5
    
6.
Bråthen G, Bjerve KS, Brodtkorb E, Bovim G (2000) Validity of carbohydrate deficient transferrin and other markers as diagnostic aids in the detection of alcohol related seizures. J Neurol Neurosurg Psychiatry 68:342-348.  Back to cited text no. 6
    
7.
Culberson JW (2006a) Alcohol use in the elderly: beyond the CAGE. Part 1 of 2: prevalence and patterns of problem drinking. Geriatrics 61:23-27.  Back to cited text no. 7
    
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Culberson JW (2006b) Alcohol use in the elderly: beyond the CAGE. Part 2: Screening instruments and treatment strategies. Geriatrics 61:20-26.  Back to cited text no. 8
    
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Fagan KJ, Irvine KM, McWhinney BC, Fletcher LM, Horsfall LU, Johnson L, O'Rourke P, Martin J, Scott I, Pretorius CJ, Ungerer JP, Powell EE (2014) Diagnostic sensitivity of carbohydrate deficient transferrin in heavy drinkers. BMC Gastroenterol 14:97.  Back to cited text no. 9
    
10.
Fleming MF, Anton RF, Spies CD (2004) A review of genetic, biological, pharmacological, and clinical factors that affect carbohydrate-deficient transferrin levels. Alcohol Clin Exp Res 28:1347-1355.  Back to cited text no. 10
    
11.
French Alcohol Society (2015) Alcohol abuse : screening, diagnosis and treatment. Alcohol Addictol 375-384  Back to cited text no. 11
    
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French Alcohol Society (2013) What are the screening tools used to detect alcohol abuse in the elderly? Alcohol Addictol 36:247-251.   Back to cited text no. 12
    
13.
Golka K, Wiese A (2004) Carbohydrate-deficient transferrin (CDT)-a biomarker for long-term alcohol consumption. J Toxicol Environ Health B Crit Rev 7:319-337.  Back to cited text no. 13
    
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Hermansson U, Helander A, Huss A, Brandt L, Rönnberg S (2000) The Alcohol Use Disorders Identification Test (AUDIT) and carbohydrate-deficient transferrin (CDT) in a routine workplace health examination. Alcohol Clin Exp Res 24:180-187.  Back to cited text no. 16
    
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Koch H, Meerkerk GJ, Zaat JO, Ham MF, Scholten RJ, Assendelft WJ (2004) Accuracy of carbohydrate-deficient transferrin in the detection of excessive alcohol consumption: a systematic review. Alcohol Alcohol 39:75-85.  Back to cited text no. 18
    
19.
Mundle G, Ackermann K, Munkes J, Steinle D, Mann K (1999) Influence of age, alcohol consumption and abstinence on the sensitivity of carbohydrate-deficient transferrin, gamma-glutamyltransferase and mean corpuscular volume. Alcohol Alcohol 34:760-766.  Back to cited text no. 19
    
20.
Paille F (2014) Guidelines "elderly and alcohol consumption". Alcool Addictolol 36:225-231.  Back to cited text no. 20
    
21.
Salaspuro M (1999) Carbohydrate-deficient transferrin as compared to other markers of alcoholism: a systematic review. Alcohol 19:261-271.  Back to cited text no. 21
    
22.
Schellenberg F, Schwan R, Mennetrey L, Loiseaux MN, Pagès JC, Reynaud M (2005) Dose-effect relation between daily ethanol intake in the range 0-70 grams and %CDT value: validation of a cut-off value. Alcohol Alcohol 40:531-534.  Back to cited text no. 22
    
23.
Schwan R, Albuisson E, Malet L, Loiseaux MN, Reynaud M, Schellenberg F, Brousse G, Llorca PM (2004) The use of biological laboratory markers in the diagnosis of alcohol misuse: an evidence-based approach. Drug Alcohol Depend 74:273-279.  Back to cited text no. 23
    
24.
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Conflicts of interest
None declared.
Author contributions
SC wrote the entire manuscript and approved the final version of the manuscript before publication.
Acknowledgments
We would like to thank Groupe Hospitalier Régional Mulhouse Sud Alsace for helps for this trial.
Plagiarism check
This paper was screened twice using CrossCheck to verify originality before publication.
Peer review
This paper was double-blinded and stringently reviewed by international expert reviewers.


    Figures

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    Tables

  [Table 1], [Table 2], [Table 3]



 

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