Study protocol; thyroid hormone replacement for untreated older adults with subclinical hypothyroidism - a randomised placebo controlled trial (TRUST)

Background: Subclinical hypothyroidism (SCH) is a common condition in elderly people, defined as elevated serum thyroid-stimulating hormone (TSH) with normal circulating free thyroxine (fT4). Evidence is lacking about the effect of thyroid hormone treatment. We describe the protocol of a large randomised controlled trial (RCT) of Levothyroxine treatment for SCH. Methods: Participants are community-dwelling subjects aged ≥65 years with SCH, diagnosed by elevated TSH levels (≥4.6 and ≤19.9 mU/L) on a minimum of two measures ≥ three months apart, with fT4 levels within laboratory reference range. The study is a randomised double-blind placebo-controlled parallel group trial, starting with levothyroxine 50 micrograms daily (25 micrograms in subjects <50Kg body weight or known coronary heart disease) with titration of dose in the active treatment group according to TSH level, and a mock titration in the placebo group. The primary outcomes are changes in two domains (hypothyroid symptoms and fatigue / vitality) on the thyroid-related quality of life questionnaire (ThyPRO) at one year. The study has 80% power (at p = 0.025, 2-tailed) to detect a change with levothyroxine treatment of 3.0% on the hypothyroid scale and 4.1% on the fatigue / vitality scale with a total target sample size of 750 patients. Secondary outcomes include general health-related quality of life (EuroQol), fatal and non-fatal cardiovascular events, handgrip strength, executive cognitive function (Letter Digit Coding Test), basic and instrumental activities of daily living, haemoglobin, blood pressure, weight, body mass index and waist circumference. Patients are monitored for specific adverse events of interest including incident atrial fibrillation, heart failure and bone fracture. Discussion: This large multicentre RCT of levothyroxine treatment of subclinical hypothyroidism is powered to detect clinically relevant change in symptoms / quality of life and is likely to be highly influential in guiding treatment of this common condition. Trial registration: Clinicaltrials.gov NCT01660126; registered 8th June 2012

Incorporating Baseline Outcome Data in Individual Participant Data Meta-Analysis of Non-randomized Studies.

Background In non-randomized studies (NRSs) where a continuous outcome variable (e.g., depressive symptoms) is assessed at baseline and follow-up, it is common to observe imbalance of the baseline values between the treatment/exposure group and control group. This may bias the study and consequently a meta-analysis (MA) estimate. These estimates may differ across statistical methods used to deal with this issue. Analysis of individual participant data (IPD) allows standardization of methods across studies. We aimed to identify methods used in published IPD-MAs of NRSs for continuous outcomes, and to compare different methods to account for baseline values of outcome variables in IPD-MA of NRSs using two empirical examples from the Thyroid Studies Collaboration (TSC). Methods For the first aim we systematically searched in MEDLINE, EMBASE, and Cochrane from inception to February 2021 to identify published IPD-MAs of NRSs that adjusted for baseline outcome measures in the analysis of continuous outcomes. For the second aim, we applied analysis of covariance (ANCOVA), change score, propensity score and the naïve approach (ignores the baseline outcome data) in IPD-MA from NRSs on the association between subclinical hyperthyroidism and depressive symptoms and renal function. We estimated the study and meta-analytic mean difference (MD) and relative standard error (SE). We used both fixed- and random-effects MA. Results Ten of 18 (56%) of the included studies used the change score method, seven (39%) studies used ANCOVA and one the propensity score (5%). The study estimates were similar across the methods in studies in which groups were balanced at baseline with regard to outcome variables but differed in studies with baseline imbalance. In our empirical examples, ANCOVA and change score showed study results on the same direction, not the propensity score. In our applications, ANCOVA provided more precise estimates, both at study and meta-analytical level, in comparison to other methods. Heterogeneity was higher when change score was used as outcome, moderate for ANCOVA and null with the propensity score. Conclusion ANCOVA provided the most precise estimates at both study and meta-analytic level and thus seems preferable in the meta-analysis of IPD from non-randomized studies. For the studies that were well-balanced between groups, change score, and ANCOVA performed similarly

Drug prescription rates in secondary cardiovascular prevention in old age: Do vulnerability and severity of the history of cardiovascular disease matter?

<p><i>Objective</i>: To assess the influence vulnerability and severity of cardiovascular disease (CVD), on prescription rates of secondary cardiovascular preventive drugs in old age.</p> <p><i>Design:</i> Population-based observational study within the ISCOPE study. <i>Setting:</i> General practices in the Netherlands.</p> <p><i>Subjects</i>: A total of 1350 patients with a history of CVD (median age 81 years, 50% female).</p> <p><i>Main outcome measures.</i> One-year prescription rates of lipid-lowering drugs and antithrombotics were obtained from the electronic medical records of 46 general practitioners (GPs). Prescription of both drugs for ≥ 270 days per year was considered optimal. GPs made a judgement of vulnerability. Severity of CVD was expressed as major (myocardial infarction, stroke, or arterial surgery) versus minor (angina, transient ischaemic attack, or claudication).</p> <p><i>Results</i>: GPs considered 411 (30%) participants to be vulnerable and 619 (55%) participants had major CVD. Optimal treatment was prescribed to 680 (50%) participants, whereas 370 (27%) received an antithrombotic drug only, 53 (4%) a lipid-lowering drug only, and 247 (18%) received neither. Optimal treatment was lower in participants aged ≥ 85 years (OR 0.37 [95% CI 0.29–0.48]), in females (OR 0.63 [0.50–0.78]), in vulnerable persons (OR 0.79 [0.62–0.99]) and in participants with minor CVD (OR 0.65 [0.53–0.81]). Multivariate ORs remained similar whereas vulnerability lost its significance (OR 0.88 [0.69–1.1]).</p> <p><i>Conclusion</i>: In old age, GPs’ judgement of vulnerability is not independently associated with lower treatment rates of both lipid-lowering drugs and antithrombotics, whereas a history of minor CVD is. Individual proactive re-evaluation of preventive treatment in older (female) patients, especially those with a history of minor CVD, is recommended.Key points</p><p>Prescriptions of lipid-lowering drugs and antithrombotics in secondary cardiovascular prevention tend to decline with age.</p><p>In this study with median age 81 years, 50% of participants received optimal treatment with both lipid-lowering drugs and antithrombotics.</p><p>GPs’ judgement of vulnerability was not independently associated with optimal treatment.</p><p>A history of less severe cardiovascular disease was independently associated with lower prescription rates of lipid-lowering drugs and antithrombotics.</p><p>Proactive individual re-evaluation of cardiovascular preventive treatment in older (female) patients, especially patients with less severe cardiovascular disease, is recommended.</p><p></p> <p>Prescriptions of lipid-lowering drugs and antithrombotics in secondary cardiovascular prevention tend to decline with age.</p> <p>In this study with median age 81 years, 50% of participants received optimal treatment with both lipid-lowering drugs and antithrombotics.</p> <p>GPs’ judgement of vulnerability was not independently associated with optimal treatment.</p> <p>A history of less severe cardiovascular disease was independently associated with lower prescription rates of lipid-lowering drugs and antithrombotics.</p> <p>Proactive individual re-evaluation of cardiovascular preventive treatment in older (female) patients, especially patients with less severe cardiovascular disease, is recommended.</p

Univariate all-cause mortality risks for sex-dependent quartiles of laboratory results included in the laboratory profile (n = 562).

<p>Data represent hazard ratios and 95% confidence intervals, calculated with the univariate Cox-proportional hazard model.</p><p>Laboratory results are divided into sex-dependent quartiles.</p><p>25th, 50th and 75th percentile limits of laboratory results stratified for sex:</p><p>Hemoglobin: male 12.5–13.4–14.2 g/dL; female 12.0–12.8–13.6 g/dL.</p><p>High-density lipoprotein cholesterol: male 35.5–42.5–51.7 mg/dL; female: 41.7–52.1–61.8 mg/dL.</p><p>Alanine transaminase: male 11–15–20 U/L; female: 11–14–17 U/L.</p><p>Albumin: male: 4.0–4.2–4.4 g/dL; female: 4.0–4.2–4.4 g/dL.</p><p>Creatinin clearance: male: 39.4–47.2–53.9 ml/min; female: 36.8–43.4–50.8 ml/min.</p><p>C-reactive protein: male: 2–4–8 mg/L; female: 1–4–8 mg/L.</p><p>Homocysteine: male: 1.47–19.8–25.6 mg/L; female: 15.0–17.9–22.8 mg/L.</p>*<p>highest to lowest quartile.</p

Baseline characteristics of the study population at age 85 years stratified according to the number of abnormal laboratory results.

<p>Continuous data are presented as median (IQR); p for trend values were obtained by Jonckheere Terpstra tests.</p><p>Categorical data are presented as number (%); p for trend values were obtained by Linear by Linear tests.</p>*<p>cancer, myocardial infarction, stroke, dementia, diabetes, chronic obstructive pulmonary disease, Parkinson’s disease, hip fracture, arthritis.</p

Kaplan Meier cumulative mortality curves for all cause mortality according to the three models.

<p>(A) laboratory profile based on sex specific quartiles of the seven included laboratory values, (B) sex specific quartiles of gait speed and (C) sex specific quartiles of instrumental activities of daily living (IADL) at age 85 years. <b>A </b><b>- - -</b> no laboratory abnormalities n = 144, <b>-----</b>1 laboratory abnormality n = 165, <b>-----</b>2–4 laboratory abnormalities n = 216, <b>-----</b>5–7 laboratory abnormalities n = 37. <b>B - - -</b> 6-meter gait speed male 0.69 –1.37 m/s; female 0.89–1.61 m/s n = 139, <b>-----</b> 6-meter gait speed male 1.38–1.81 m/s; female 1.61–2.15 m/s n = 142, <b>-----</b> 6-meter gait speed male 1.81–2.81 m/s; female 2.16–3.95 n = 141, <b>-----</b>6-meter gait speed male 2.91–13.0 m/s; female 4.00–13.00 m/s n = 140. <b>C - - -</b> IADL-score male 9–11; female 9–12 n = 136, <b>-----</b> IADL-score male 12–16; female 13–18 n = 141, <b>-----</b> IADL-score male 17–24; female 19–28 n = 145, <b>-----</b> IADL-score male 25–36; female 29–36 n = 139.</p