determining the effective factors on tsh level in the

JP Journal of Biostatistics

© 2020 Pushpa Publishing House, Prayagraj, India

http://www.pphmj.com

http://dx.doi.org/10.17654/BS017020477

Volume 17, Number 2, 2020, Pages 477-490 ISSN: 0973-5143

Received: July 13, 2020; Accepted: August 12, 2020

Keywords and phrases: hyperthyroidism, radioactive iodine, generalized estimating equations,

mixed effects model.

∗Corresponding author

DETERMINING THE EFFECTIVE FACTORS ON TSH

LEVEL IN THE PATIENTS WITH GRAVES’

DISEASE: A LONGITUDINAL STUDY

Atefeh Malekhoseiny1, Mohammadreza Rezvanfar

2, Azam Moslemi

1,

Fatemeh Rafiei3, Mohammad Rafiei

1,*, Faezeh Rezvanfar

4 and

Kosar Hajdezfulian4

1Department of Biostatistics

School of Medical Sciences

Arak University of Medical Sciences

Arak, Iran

e-mail: [email protected]

[email protected]

[email protected]

2Department of Endocrinology

Thyroid Disorders Research Center


Arak, Iran


3Department of Biostatistics and Epidemiology

School of Health

Scientific Research Center

Tehran University of Medical Sciences

Tehran, Iran


Atefeh Malekhoseiny et al. 478

4School of Medicine


Arak, Iran


[email protected]

Abstract

Introduction: One of the most important thyroid disorders is

hyperthyroidism resulting from Graves’s disease. One of the most

common therapies is using radioactive iodine, called iodine therapy.

This study aims to identify the factors effective on TSH level variation

in the patients with Graves’s disease under treatment with radioactive

iodine.

Materials and Methods: This is a longitudinal-observational study.

201 patients with Graves’s disease, who were under treatment with

radioactive iodine, were entered into the study. TSH levels in the

patients’ blood were measured prior to the treatment with radioactive

iodine, and 2, 4 and 6 months after the treatment. The marginal model

by generalized estimating equations, and mixed effects model were

fitted in order to analyze the effect of each predictive variable on the

trend of TSH levels. The statistical analysis was performed by using

R3.5.2 software, and for all the tests, the level of significance was

considered 0.05.

Results: Mean age of patients was 37.54 ± 13.66 years, out of which

61.7% were female. In both the methods, the interaction of time

duration, and baseline TSH were significant ( ).05.0<P In addition,

fitting the mixed effect model showed that the dose of Methimazole

had significant effect on the TSH level ( ).05.0<P

Conclusions: In this study, results of both the models were similar.

The effects of baseline TSH, dose of administered Methimazole and

the interaction of time and the dose of radioactive iodine led to the

increase of TSH in the patient’s bloodstream.

Determining the Effective Factors on TSH Level … 479

Introduction

The thyroid disorders belong to the most common endocrine disorders

in the world [1]. The thyroid gland controlling mechanism is as such: the

reduction in amount of the Thyroid hormones ( )43 and TT leading to the

increase of producing the thyroid stimulating hormone (TSH), and vice versa

(2, 3). Hyperthyroidism is a case where the thyroid gland is over-activated.

This may lead to the reduction or even lack of TSH in the patient’s

bloodstream. Its incidence occurs in women 10 times more than men [4, 5].

The incidence of hyperthyroidism in the world has been reported to be

0.2% to 1.3% [6]. In a study, it has been reported that the incidence of

hyperthyroidism in an Iranian adult population was 1.6% [7]. The major

causes of hyperthyroidism are Graves’s disease (GD), multi-nodular toxic

goiter, and the toxic adenomas of the thyroid gland [8].

GD is an auto-immunity disorder. Its main cause is the formation of

antibodies against thyrotropin receptors (TSHR) which activate the thyroid

cells to increase their activities. Often, genetic factors, stress, pregnancy, and

inflammation are regarded as the main causes of GD [9]. Surgical operation,

taking anti-thyroid drugs, and using radioactive iodine (I131) are the main

therapies for GD. The method of iodine therapy is more attracting due to its

ease of application, repeatability, cheapness, fewer side effects and the less

probability of relapse after the treatment. On the other hand, the therapeutic

methods are not completely safe, and it may result into some side-effects

such as the prevalence of hypothyroidism in the patients under treatment.

Also, the attempts of determining the optimum dose of I131 without

considering hypothyroidism side-effects, the treatment of hyperthyroidism

will remain useless [10, 11].

The longitudinal data is repeated observations of the studied individuals

over a time period. It is assumed that in this series of data the individuals

are independent; but, everyone’s responses over time are correlated. In

these studies, often, with the passage of time, correlation of everyone’s

observations reduces; and, the assumption of variance homogeneity is not


set. Also, the possibility of lost data, and the number of unequal repetitions

especially in clinical trials cannot be ignored [12, 13].

The marginal model with generalized estimating equations (GEE), and

mixed effects model (MEM) are the best methods of analyzing the

longitudinal data [14-16].

The main objective of the present study is to identify the factors

effective on the variation of TSH levels in the patients with GD, who have

gone under treatment with radioactive iodine, by using the method of GEE,

and MEM.

Methods

201 patients with hyperthyroidism caused by GD, who were under

treatment with I131 according to the physician’s diagnosis, were entered in

this longitudinal study. The diagnosis of GD was based on elevated higher

free thyroxine (FT4) with suppressed TSH level and clinical examination

findings (such as diffusely enlarged goiter and typical signs and symptoms of

hyperthyroidism) with documented presence of thyroid autoantibodies. After

diagnosis of hyperthyroidism, the patients took at least for a month anti-

thyroid Methimazole drug (MMI) until the thyroid performance became

natural, i.e., euthyroidism and patients get ready to receive I131. After

euthyroidism, and prior to iodine therapy, every patient’s TSH level, was

recorded. Five days after discontinuity of MMI, iodine therapy started

(patients received no medication for 5 days, because antithyroid drugs

reduce iodine uptake by the thyroid, and it is necessary to stop taking drugs

before initiating iodine therapy). The patients were studied for a maximum

period of consecutive months. Every two months, the patients’ TSH levels in

their bloodstream were measured and recorded. Also, the variables of age

(year), gender (male or female), smoking status (smoker or non-smoker), and

the thyroid gland size 0 (small, no palpable or visible goiter), 1 (moderate, a

mass in the neck that is consistent with an enlarged thyroid which is palpable

but not visible when the neck is in the normal position) and 2 (large, a

swelling in the neck that is visible when the neck is in the normal position


and is consistent with an enlarged thyroid when the neck is palpated)) [17],

the administered dose of MMI (the number of tablets 5 mg), and the

administered dose of I131 (mCi) were recorded for every patient. Then the

marginal model of GEE used exchangeable correlation structure. The MEM

model only with the random effect of subject variable and fixed effect time

used the Gamma distribution, and the log link function. Both of the models

were fit to the data for investigation of the main effects of age, gender,

smoking status, thyroid gland size, administered dose of MMI, administered

dose of I131, TSH level after completion of consuming MMI (baseline

TSH), time and the interaction of time and dose of the I131 on TSH level

variations in the patients’ bloodstreams under treatment with iodine therapy

(TSH level). The statistical analysis was performed by using R3.5.2

software. The level of significance was considered 0.05 for all the tests.

Marginal model by generalized estimating equations and mixed effects

model

GEE method focuses on the average response variation of the population

over time, and on the effects of the predictive variables. In this method,

needless of assuming a specific parametric distribution for the response

variable, the mean structures and their variance/covariance can be separately

and without any limitation determined. The response variable’s mean can be

fitted into a link function as a linear function of the determined predictive

variables [18-20].

A MEM can be considered as a multi-level or hierarchical model,

in which the 1st level observations (everyone’s observations) are nested

in the 2nd level observations (different individuals). MEM investigates

individually the trend of response variations, and considers the heterogeneity

of individuals by adding into model the random effects of the predictive

variables in the analysis. Contrary to the method of GEE, in this model, there

should be considered a proper parametric distribution for each response

variable [20, 21].


Ethical considerations

In this study, all ethical regulations have been observed. Participation in

this study had no financial burden on patients and patients’ private and

personal information had been kept confidential.

Results

The mean TSH level before MMI administration and at the time of

diagnosis was 0.024 ± 0.018. Table 1 shows the descriptive statistics of the

patients’ demographic and clinical specifications. As it can be seen, a

majority of the patients were non-smoker women. TSH level Pearson

correlation coefficients in the three times of measurement are shown in

Figure 1. Baseline TSH correlated significantly with TSH level 2 and 4

months after iodine therapy ( ).002.0,0001.0 == PP Also, TSH level 2

months after iodine therapy was significantly correlated with TSH level 4

and 6 months after iodine therapy ( ).009.0,0001.0=P

Table 1. The descriptive statistics of studied patients’ demographic and

clinical specifications

Variable Class No. Percentage Mean Standard deviation

Male 77 38.3 Gender

Female 124 61.7 - -

Non-smoker 176 87.6 Smoking status

Smoker 25 12.4 - -

0 21 10.4

1 46 22.9 Thyroid gland size

2 134 66.7

- -

Age (year) - - - 37.54 13.66

Dose of MMI - - - 4.44 1.24

Dose of I131 - - - 11.07 4.03

Baseline TSH - - - 3.21 7.47


Figure 1. The observed Pearson correlation coefficient of TSH levels during

different measurement intervals for patients with GD (P-value).

Mean TSH variation over time is shown in Figure 2 and TSH variation

over time for every patient is shown in Figure 3. As it can be seen from these

figures, TSH is increasing with time. The absence of some patients in the

fourth month for visit and exit, some other patients after this time of the

study created the gap in Figure 3.

Figure 2. Mean TSH level variation over time for patients with GD.


Figure 3. TSH level variation over time for any patient with GD.

The results of fitting the marginal model by the method of GEE are

presented in Table 2, and those of fitting MEM are presented in Table 3.

Table 2. The results of fitting GEE model on TSH level of patients with GD

Variables Coefficient estimate Standard error P-value

Age(year) -0.003 0.01 0.710

Male - - - Gender

Female -0.26 0.30 0.387

Non-smoker - - - Smoking status

Smoker 0.60 0.43 0.165

0 - - -

1 0.19 0.35 0.589 Thyroid gland size

2 -0.12 0.39 0.760

Baseline TSH 0.05 0.01 0.0001

Dose of MMI 0.10 0.07 0.172

Dose of I131 0.05 0.06 0.405

Time 0.71 0.15 0.0001

Time∗ dose of I131 -0.03 0.01 0.030

QIC 1837.376


Table 3. The results of fitting MEM on TSH level of patients with GD

Variables Coefficient estimate Standard error P-value

Age (year) -0.007 0.01 0.467

Male - - - Gender

Female -0.10 0.32 0.770

Non-smoker - - - Smoking status

Smoker 0.66 0.45 0.244

0 - - -

1 -0.05 0.43 0.911 Thyroid gland size

2 -0.19 0.43 0.675

Baseline TSH 0.05 0.01 0.005

Dose of MMI 0.20 0.10 0.049

Dose of I131 0.10 0.06 0.127

Time 0.66 0.15 0.0001

Time∗ dose of I131 -0.05 0.01 0.0001

QIC 1970.476

The results of the method of GEE showed that there was a significant

relationship between TSH level, and baseline TSH, so that the patients who

had 1-unit higher baseline TSH, their TSH level mean were higher (1.05

times) after treatment with I131 ( ).0001.0=P If the patients received the

average dose of I131, then TSH level increased 2.07 times during every 2

months ( ).030.0=P

The results of fitting MEM showed that there was a significant

relationship between TSH level, and baseline TSH, so that patients who have

1-unit higher baseline TSH l, had higher (1.05 times) TSH level after

treatment with iodine therapy ( ).005.0=P In the patients who had received

1 more MMI tablet, TSH level was 1.22 times greater than other patients

( ).049.0=P If the patients received the average dose of I131, then TSH

level increased 1.19 times during every 2 months ( ).001.0=P

Discussion

In this study, the effects of baseline TSH, and the interaction of time

and the dose of I131 were found significant in both of the marginal and

mixed models. Also, the regression coefficients calculated were similar in

these models. These results indicated that after the initiation of iodine


therapy with an average dose of I131 for each patient, TSH level in the

patients’ bloodstreams over time would increase. Also, the standard errors of

estimated coefficients were small and not different in these models.

According to the results of mixed effects model, the increase in the dose

of administered MMI for each patient will lead to the increase of TSH level.

This result confirms that MMI restrains the production of thyroid hormones,

as a result, and as a feedback there will be an increase of TSH.

Baek et al. in their study, examined 105 patients with major depressive

disorder over 3 months, and used linear mixed model to identify the

relationship between TSH level in the patients’ bloodstreams and

neurotropic factor brain-derived [22]. Abdi et al. conducted a study on the

individuals with natural performance of thyroid gland over 9 years, and they

used GEE to study the relationship between the performance of thyroid

gland, and the level of blood pressure in the adult population [23]. Ying et

al. discussed the linear regression methods in the analysis of ocular data in

order to determine the related factors of purview among the adolescent. The

results showed that in those studies that if the information of patients’ both

eyes is inserted; the ignorance of observations regression can lead to false

results. In such cases, GEE, and MEM show the utmost statistical power and

accuracy [24]. Strickland et al., in a study, used three methods: MEM, GEE,

and quadratic inference functions in the analysis of cluster data including the

amounts of genome and epigenome. In this study, all the three methods

showed acceptable statistical power; but, in the marginal model, diagonal

correction seemed necessary [25]. To investigate the relationship between

Stargardt’s disease characteristics, and visual ability, Kong et al. investigated

176 patients from Europe and the U.S.A. In this study, they used GEE

analytic method to estimate the temporary relationships, and they used MEM

analytic method to estimate the amount of visual ability loss over time [26].

Naseri et al., in a study, used GEE method to analyze menorrhagia

data. They also compared it with repeated measure-ANOVA, and MEM.

According to the results of this study, GEE, and MEM, having many


advantages, are very considerable for the analysis of repeated data. GEE,

especially is very appropriate to analyze the overall effects [21]. In the

present study, 62% of the patients with Graves’s disease were women. The

patients’ average age was 37.5 ± 13.7, which is in accordance to the study by

Younis [27]. But, in the study by Cheah et al., the patients’ average age with

Graves’s disease was reported 46.1 ± 1.5 [28]. Also, in the present study,

it has been shown that age, gender, and thyroid gland severity have no

significant effect on the patient’s response to treatment with radioactive

iodine, which is consistent with the study of Sun [29]. According to the

results of MEM, consuming Methimazole drug has a positive effect on the

increase of TSH level in the patients’ bloodstreams, which is consistent with

the study results by Younis [27]. Sheehan and Doi, in a study on the patients

with Graves’s disease who were under treatment with radioactive iodine,

examined the different types of hypothyroidism which occur after iodine

therapy in each patient [30]. Laurberg et al., in a study, investigated the

effect of common therapy of hyperthyroidism from Graves’s disease on

TSH-receptor autoimmunity. According to the results of this study, in all

the therapeutic methods, majority of the patients experienced remission of

TSH-receptor autoimmunity. But, in the treatment with radioactive iodine

remission of TSH-receptor autoimmunity was less prevalent [31].

Conclusions

Both the methods of GEE and MEM are very useful for the analysis of

the observations from iodine therapy in the patients with hyperthyroidism

over a given time period. In fact, in the longitudinal studies, added to

statistical inferences about the population mean over a given time by using

the method of GEE, some inferences also can be made about the paths of

response variations on the level of each individual by the help from MEM.

By this study, the effects of baseline TSH, the interaction of time and the

dose of I131, and dose of administered MMI were found significant. These

effects will increase the TSH in the patient’s bloodstream under treatment

with I131.


Acknowledgement

The present article is extracted from the Master’s thesis. It is

financially supported by Arak University of medical sciences, coded

IR.ARAKMU.REC.1396.184. There is no conflict of interest with other

organizations or individuals. We thank everyone who provided insight and

expertise that greatly assisted the research.

References

[1] M. A. Walter, M. Briel, M. Christ-Crain, S. J. Bonnema, J. Connell, D. S. Cooper,

H. C. Bucher, J. Müller-Brand and B Müller, Effects of antithyroid drugs on

radioiodine treatment: systematic review and meta-analysis of randomised

controlled trials, BMJ 334(7592) (2007), 514.

[2] H. B. Burch and D. S. Cooper, Management of Graves disease: a review, JAMA

314(23) (2015), 2544-2554.

[3] M. I. Chiamolera and F. E. Wondisford, Thyrotropin-releasing hormone and the

thyroid hormone feedback mechanism, Endocrinology 150(3) (2009), 1091-1096.

[4] S. Melmed, Williams Textbook of Endocrinology, Elsevier Health Sciences, 2016.

[5] A. G. Unnikrishnan and U. V. Menon, Thyroid disorders in India: an

epidemiological perspective, Indian Journal of Endocrinology and Metabolism

15(Suppl2) (2011), S78-S81.

[6] P. N. Taylor, D. Albrecht, A. Scholz, G. Gutierrez-Buey, J. H. Lazarus, C. M.

Dayan and O. E. Okosieme, Global epidemiology of hyperthyroidism and

hypothyroidism, Nature Reviews Endocrinology 14 (2018), 301-316.

[7] A. Aminorroaya, R. Meamar, M. Amini, A. Feizi, A. Tabatabae and E. F. Imani,

Incidence of thyroid dysfunction in an Iranian adult population: the predictor role

of thyroid autoantibodies: results from a prospective population-based cohort

study, European Journal of Medical Research 22(1) (2017), 21.

[8] D. S. Ross et al., American thyroid association guidelines for diagnosis and

management of hyperthyroidism and other causes of thyrotoxicosis, Thyroid.

26(10) (2016), 1343-1421.

[9] B. Pandiyan, S. J. Merrill, F. Di Bari, A. Antonelli and S. Benvenga, A patient-

specific treatment model for Graves’ hyperthyroidism, Theoretical Biology and

Medical Modelling 15(1) (2018), 1.


[10] Y. A. Onimode, D. M. Dairo and A. Ellmann, Pattern of presentation of Graves’

disease and response to radioiodine therapy in South African men, The Pan

African Medical Journal 29 (2018), 48.

[11] C. Regalbuto, I. Marturano, A. Condorelli, A. Latina and V. Pezzino,

Radiometabolic treatment of hyperthyroidism with a calculated dose of 131-

iodine: results of one-year follow-up, Journal of Endocrinological Investigation

32(2) (2009), 134-138.

[12] Z. Geraili-Afra, A. Abadi, J. Yazdani-Charati, S. A. Gooraji, M. Zarghami and

S. Saadat, Comparison of efficiency GEE and QIF methods for predicting factors

affecting on bipolar I disorder under complete-case in a longitudinal studies, Acta

Informatica Medica 26(2) (2018), 111.

[13] Y. Ma, M. Mazumdar and S. G. Memtsoudis, Beyond repeated measures

ANOVA: advanced statistical methods for the analysis of longitudinal data in

anesthesia research, Regional Anesthesia and Pain Medicine 37(1) (2012), 99.

[14] E. Demidenko, Mixed Models: Theory and Applications with R, John Wiley and

Sons, 2013.

[15] P. Diggle, P. J. Diggle, P. Heagerty, P. J. Heagerty, K.-Y. Liang and S. Zeger,

Analysis of Longitudinal Data, Oxford University Press, 2002.

[16] S. L. Zeger and K.-Y. Liang, Longitudinal data analysis for discrete and

continuous outcomes, Biometrics 42 (1986), 121-130.

[17] W. L. Tay, C. L. Chng, C. S. Tien, K. S. Loke, W. W. Lam, S. M. Fook-Chong

and A. K. Tong, High thyroid stimulating receptor antibody titre and large goitre

size at first-time radioactive iodine treatment are associated with treatment failure

in Graves’ disease, Ann. Acad. Med. Singapore 48 (2019), 181-187.

[18] G. M. Fitzmaurice, N. M. Laird and J. H. Ware, Applied Longitudinal Analysis,

John Wiley and Sons, 2012.

[19] P. McCullagh and J. A. Nelder, Generalized Linear Models, CRC Press, 1989.

[20] L. Wu, Mixed Effects Models for Complex Data, Chapman and Hall/CRC, 2009.

[21] P. Naseri, H. A. Majd, N. Kariman and A. Sourtiji, Comparison of generalized

estimating equations (GEE), mixed effects models (MEM) and repeated measures

ANOVA in analysis of menorrhagia data, Journal of Paramedical Sciences

7(1) (2016), 32-40.

[22] J. H. Baek, E.-S. Kang, M. Fava, D. Mischoulon, A. A. Nierenberg, D. Lee, J.-Y.

Heo and H. J. Jeon, Thyroid stimulating hormone and serum, plasma, and platelet

brain-derived neurotrophic factor during a 3-month follow-up in patients with

major depressive disorder, Journal of Affective Disorders 169 (2014), 112-117.


[23] H. Abdi, S. Gharibzadeh, E. Tasdighi, A. Amouzegar, L. Mehran, M. Tohidi and

F. Azizi, Associations between thyroid and blood pressure in euthyroid adults:

a 9-year longitudinal study, Hormone and Metabolic Research 50(3) (2018),

236-241.

[24] G.-S. Ying, M. G. Maguire, R. Glynn and B. Rosner, Tutorial on biostatistics:

linear regression analysis of continuous correlated eye data, Ophthalmic

Epidemiology 24(2) (2017), 130-140.

[25] J. C. Strickland, I.-C. Chen, C. Wang and D. W. Fardo, Longitudinal data methods

for evaluating genome-by-epigenome interactions in families, BMC Genetics

19(1) (2018), 82.

[26] X. Kong, R. W. Strauss, M. Michaelides, A. V. Cideciyan, J.-A. Sahel, B. Muñoz,

S. West and H. P. N. Scholl, Visual acuity loss and associated risk factors in the

retrospective progression of Stargardt disease study (ProgStar Report No. 2),

Ophthalmology 123(9) (2016), 1887-1897.

[27] J. Younis, The effect of anti thyroid medications on the therapeutic outcome of

I-131 in hyperthyroid patients with Graves’ disease, Egyptian J. Nucl. Med.

14(1) (2017), 28-39.

[28] S. Cheah, K. Aljenaee, N. Muhammad, L. Gavigan and M. Dooley, Outcomes

following fixed dose radioactive iodine therapy (RAI) in hyperthyroid patients

with Grave’s disease and toxic nodular disease, Endocrinol. Metab. Int. J.

3(6) (2016), 174-176.

[29] Q. Sun, S. Li, Z. Wu, J. Liu, H. Liu and K. Lu, The analysis of the affecting

factors on clinical outcome of early-onset hypothyroidism after the patients with

hyperthyroidism received 131I therapy, Journal of Nuclear Medicine 59(1) (2018),

239.

[30] M. T. Sheehan and S. A. Doi, Transient hypothyroidism after radioiodine

for Graves’ disease: challenges in interpreting thyroid function tests, Clinical

Medicine and Research 14 (2016), 40-45.

[31] P. Laurberg, G. Wallin, L. Tallstedt, M. Abraham-Nordling, G. Lundell and O.

Tørring, TSH-receptor autoimmunity in Graves’ disease after therapy with anti-

thyroid drugs, surgery, or radioiodine: a 5-year prospective randomized study,

European Journal of Endocrinology 158(1) (2008), 69-75.

determining the effective factors on tsh level in the

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