The Effectiveness of Smoking Cessation in Prediabetic Smokers
|First Received Date ICMJE||August 6, 2013|
|Last Updated Date||December 1, 2014|
|Start Date ICMJE||August 2013|
|Estimated Primary Completion Date||July 2018 (final data collection date for primary outcome measure)|
|Current Primary Outcome Measures ICMJE
||Diagnosis of diabetes mellitus by ADA criteria [ Time Frame: at least 3 years (from Aug 1, 2013) ] [ Designated as safety issue: No ]
The primary outcome is DM, defined as having repeatedly at least one of the following criteria: 1) plasma glucose ≥126 mg/dL (7.0 mmol/L) in the fasting state; 2) plasma glucose ≥200 mg/dL (11.1 mmol/L) randomly with hyperglycemic symptoms or two hours after a 75-g oral glucose load; 3) A1C ≥6.5%;20 or under medications for physician-diagnosed DM.
|Original Primary Outcome Measures ICMJE||Same as current|
|Change History||Complete list of historical versions of study NCT01926041 on ClinicalTrials.gov Archive Site|
|Current Secondary Outcome Measures ICMJE
|Original Secondary Outcome Measures ICMJE||Same as current|
|Current Other Outcome Measures ICMJE
||All-cause mortality [ Time Frame: at least 3 years (from Aug 1, 2013) ] [ Designated as safety issue: No ]
Deaths are ascertained by computer linkage to the national death registry (death certificates were created by the Department of Health, Taiwan) using ID numbers and these death certificates have been validated.
|Original Other Outcome Measures ICMJE||Same as current|
|Brief Title ICMJE||The Effectiveness of Smoking Cessation in Prediabetic Smokers|
|Official Title ICMJE||Community-based Pilot Study of the Effectiveness of Smoking Cessation for Prediabetes|
Smoking is one of major risk factor for incident type 2 diabetes mellitus (DM), and smoking cessation can improve insulin resistance. Nowadays, the second-generation cessation program in Taiwan brings higher accessibility. However, there is little evidence on the long-term health outcomes of smoking cessation for the prediabetics in the community.
This project is of five-year design. The investigators plan to recruit at least 596 prediabetic smokers and 600 prediabetic non-smokers from communities. Initially, a cross-sectional analysis will be performed to investigate the physiological and psychological characteristics in prediabetic smokers. All participants are provided with standardized diet, lifestyle education, and skills of body weight self-management, with prospective follow-up every 3-6 months. Individuals may voluntarily attend smoking cessation program. Cox regression models and Kaplan-Meier methods will be used to investigate the effectiveness of the smoking cessation and body weight self-management in prediabetics regarding new-onset DM risk, glucose control, cardiovascular events, chronic kidney diseases, chronic hepatitis or cirrhosis, malignancy, and the relevant physiological and psychological parameters of interest.
The investigators plan to recruit the study participants from 1) individuals who had abnormal glucose data at employment health examination or adult preventive care service in about 20 communities, including Yunlin, Changhua, Chiayi, and Taipei; 2) patients who has past history of metabolic syndrome and has been regularly followed-up at National Taiwan University Hospital and its Yun-Lin branch. All participants should give informed consent for this project and medical record review, with personal data protected.
A history of diabetes, hypertension, FTND, alcohol consumption, physical activity, depression, sleep quality, and current medications is collected through standardized personal interview. Prediabetics are those repeatedly having either of the following: 1) plasma glucose 100 to 125 mg/dL (5.6 to 6.9 mmol/L) in the fasting state; 2) plasma glucose 140 to 199 mg/dL (7.8 to 11.0 mmol/L) two hours after a 75-g oral glucose load; 3) glycosylated hemoglobin (A1C) 5.7% to 6.4%, in the absence of diabetic medications. Prediabetics who smoke ≥10 CPD for at least 6 months are classified as prediabetic smokers. Prediabetic non-smokers are also recruited.
According an online sample size calculator (www.openepi.com), the investigators estimate to recruit at least 596 prediabetic smokers, in case 33% (199) of them joining the smoking cessation program, to reach a 90% power and two-sided confidence interval 95% for the detection of a 50% reduction from a risk for incident DM at 3-year follow-up.17 Besides, the investigators intend to recruit a total of 600 prediabetic non-smokers, including past smokers, for baseline analysis.
Body height and weight are measured using a single stadiometer, and body mass index (BMI) was calculated. The participants are classified as either normal or underweight (BMI <23 kg/m2), overweight (BMI 23 to 24.9 kg/m2), or obese (BMI ≥25 kg/m2), according to the World Health Organization criteria for Asian populations. Waist circumference is taken at the end of exhalation in the horizontal plane at the midway point between the inferior margin of the lowest rib and the iliac crest. Central obesity is defined as a waist circumference ≥90 cm for men or ≥80 cm for women, according to the criteria for metabolic syndrome used in Taiwan (www.hpa.gov.tw). Blood pressure (BP) is measured with an electronic sphygmomanometer with the patient seated after resting for at least ten minutes. Each participant undergoes laboratory testing after fasting for at least ten hours. Serological tests include serum hepatitis B surface antigen, serum antibody to hepatitis C virus, and hepatitis B e antigen, determined via a microparticle enzyme immunoassay (Abbott Laboratories, Illinois, USA). Hepatitis B viral load for hepatitis B carriers is measured with a COBAS TaqMan real-time polymerase chain reaction assay (Roche Diagnostics, Basel, Switzerland), detecting an upper limit of 640,200,000 copies/mL and a lower limit of 35 copies/mL (1 copies/mL = 0.1718 IU/mL). Serum adiponectin levels (in μg/mL) are determined by using the Procarta Cytokine Assay Kit (Affymetrix, Inc., California, USA) as in our recent report.
Plasma glucose levels are determined through the hexokinase method (1 mg/dL = 0.0555 mmol/L). Serum fasting insulin levels are measured using the COBAS electrochemiluminescence immunoassay (Roche Diagnostics, Basel, Switzerland) (1 μIU/mL = 6.945 pmol/L). Insulin resistance scores are determined by the homeostasis model assessment of insulin resistance (HOMA-IR),23 as calculated by the following formula: HOMA-IR score = fasting insulin (μIU/mL) × fasting glucose (mg/dL)/405. Participants will be categorized as insulin resistant if the HOMA-IR is 2.5 or higher. Plasma lipid, alanine aminotransferase (ALT), and creatinine levels are measured using a Hitachi 7150 Automated analyzer (Hitachi, Tokyo, Japan). Estimated glomerular filtration rate (eGFR) is calculated using the four-variable version of the Modification of Diet in Renal Disease Study equation for Chinese Patients.25 Briefly, eGFR (ml/min per 1.73 m2) = 175 × (serum creatinine -1.234) × (age -0.179) × 0.79 (if female). The hypertriglyceridemia is defined as a plasma triglycerides level ≥150 mg/dL (1.70 mmol/L); and the hypercholesterolemia is defined as a plasma total cholesterol level ≥200 mg/dL (5.18 mmol/L). The low high-density lipoprotein cholesterol (HDL-C) is defined as a serum HDL level <40 mg/dL (1.04 mmol/L) in men and <50 mg/dL (1.29 mmol/L) in women.
Metabolic syndrome is defined clinically, based on the presence of three or more of the American Heart Association/National Heart Lung Blood Institute (AHA/NHLBI) criteria: (i) central obesity; (ii) hypertriglyceridemia or on drugs for elevated triglycerides; (iii) a low HDL-C level or on drugs for reduced HDL-C; (iv) high BP (≥130/85 mm Hg) or on antihypertensive drugs; and (v) a high fasting plasma glucose or taking anti-diabetic drugs for hyperglycemia. The International Diabetes Federation (IDF) criteria are also applied when defining metabolic syndrome, if participants have central obesity plus any two of the other four components.
For descriptive analyses, values are presented as either a number (percent) or mean ± standard deviation (SD). For univariate analyses, categorical data are compared by means of the χ2 test or Fisher exact test. Continuous variables are compared using the two-sample Student's t-test. Statistical significance levels are determined by two-tailed tests (P value < 0.05). In the end of enrollment (July of 2015), we will compare baseline characteristics among prediabetic smokers and prediabetic non-smokers, stratified by gender and BMI groups. Subgroup analysis will explore the association between adipocytokines, BMI, metabolic factors and viral load for prediabetic hepatitis B carriers.
Changes in smoking habit for prediabetic smokers are recorded every 3 to 6 months. In the end of follow-up, hazard ratios (HRs) and 95% confidence intervals (95% CIs) of smoking cessation for incident DM risk or other outcome parameters during a 3 to 5-year follow-up period are estimated by multivariate Cox regression models after controlling age, gender, BMI (time-varying covariate) or body weight change (gainer, reducer, maintainer), BP, lipids, current medications, plasma ALT level, eGFR, daily coffee consumption, alcohol consumption, physical activity, depression, and sleep quality. Both intention-to-treat analysis and per-protocol analysis will be performed (Figure 1a, 1b). The former is based on the initial group assignment and not on the treatment eventually received. In the latter analysis, only participants who complete the entire clinical trial according to the protocol are counted towards the final results. That is, the independent variable "smoking cessation" reserves only for prediabetic smokers who succeed in quitting and keeping no relapse. For those who fail in quitting or keeping no relapse, they are still classified as self-management group and the individual follow-up period is from the study enrollment.
We assume missing values over time as missing at random and do listwise deletion. We will test the assumption of proportional hazards by Kaplan-Meier curves for time fixed covariates, and by creating selected time dependent variables inside PROC PHREG with PROPORTIONALITY_TEST statement. Stratification analysis by baseline BMI group may be done. Additive and multiplicative interaction between change in smoking status and body weight on DM risk will also be estimated. Subgroup follow-up analysis will explore the association between change in adipocytokines, BMI, metabolic factors and viral load in prediabetic hepatitis B carriers. Unadjusted Kaplan-Meier survival curves of liver cancer for quitters versus non-quitters will be drawn. All of the abovementioned statistical analyses are performed with SAS software version 9.3 (SAS Institute Inc., Cary, NC, USA).
|Study Type ICMJE||Interventional|
|Study Phase||Not Provided|
|Study Design ICMJE||Allocation: Non-Randomized
Intervention Model: Parallel Assignment
Masking: Open Label
Primary Purpose: Prevention
|Study Arm (s)||
* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
|Recruitment Status ICMJE||Recruiting|
|Estimated Enrollment ICMJE||1200|
|Estimated Completion Date||July 2018|
|Estimated Primary Completion Date||July 2018 (final data collection date for primary outcome measure)|
|Eligibility Criteria ICMJE||
|Ages||30 Years to 75 Years|
|Accepts Healthy Volunteers||No|
|Listed Location Countries ICMJE||Taiwan|
|Removed Location Countries|
|NCT Number ICMJE||NCT01926041|
|Other Study ID Numbers ICMJE||201303041RINB|
|Has Data Monitoring Committee||Yes|
|Responsible Party||National Taiwan University Hospital|
|Study Sponsor ICMJE||National Taiwan University Hospital|
|Collaborators ICMJE||National Science Council, Taiwan|
|Information Provided By||National Taiwan University Hospital|
|Verification Date||December 2014|
ICMJE Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP