IGFBP3 ratio in adult population in the Czech Republic

Clinica Chimica Acta 444 (2015) 271–277

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Reference values of IGF1, IGFBP3 and IGF1/IGFBP3 ratio in adult population in the Czech Republic Radek Kucera ⁎, Ondrej Topolcan, Ladislav Pecen, Judita Kinkorova, Sarka Svobodova, Jindra Windrichova, Radka Fuchsova a b

Laboratory of Immunoanalysis, Faculty Hospital Pilsen, Czech Republic Medical Faculty Pilsen, Charles University, Prague, Czech Republic

a r t i c l e

i n f o

Article history: Received 24 January 2015 Accepted 20 February 2015 Available online 2 March 2015 Keywords: IGF1 IGFBP3 IGF1/IGFBP3 ratio Adult population Reference values

a b s t r a c t Background: IGF1 is responsible for regulation of growth, metabolism and differentiation of human cells. IGFBP3 is the most abundant of the carrier proteins for IGF1 in the blood. IGF1/IGFBP3 molar ratio is an indicator of IGF1 bioavailability. We decided to create a file of reference ranges of IGF1, IGFBP3 and IGF1/IGFBPP3 ratio for the adult Czech population across the age spectrum. Methods: We selected a group of 1022 subjects, 467 males and 555 females (ages 20–98 years), from several regions in the Czech Republic. The group consisted of blood donors and patients undergoing regular preventive examinations. Serum levels of IGF1 and IGFBP3 were measured using the following radioimmunoassay kits: IRMA IGF1 (Immunotech, Marseille, France) and IRMA IGFBP3 (Immunotech, Prague, Czech Republic). The IGF1/IGFBP3 ratio was also calculated. The following groups of patients were excluded: patients with diabetes, high blood glucose, high insulin levels, post-surgery patients, polymorbid patients, and subjects with oncological diseases. Subjects were divided into seven age-groups. Changes in the levels of observed analytes in each decade across the age spectrum were evaluated. All statistical analyses were performed by SAS 9.3 (Statistical Analysis Software release 9.3; SAS Institute Inc., Cary, NC, USA). Results: All three parameters IGF1, IGFBP3 and IGF1/IGFBP3 decreased in parallel with decrease in age: p b 0.0001, r = − 0.64, − 0.35 and − 0.54, respectively. The dynamics of the decline was different between males and females. Linear regression models with age as independent variable fitted by gender are displayed in Fig. 1. Nonparametric reference interval curves (medians and 2.5th–97.5th percentiles) for IGF1, IGFBP3 and IGF1/IGFBP3 ratio as function of age by gender are displayed in Fig. 2(a,b,c). All medians and 2.5th–97.5th percentiles were plotted by cubic spline. For males, linear regression models were as follows: IGF1 = 291.34619 − 2.41211 × age, IGFBP3 = 2931.62778 − 6.11659 × age, IGF1/IGFBP3 = 0.02897 − 0.00021213 × age. For females, we plotted the following: IGF1 = 241.67406 − 1.98466 × age, IGFBP3 = 3688.60561 − 16.39560 × age, IGF1/ IGFBP3 = 0.02029 − 0.00013233 × age. IGF1 was statistically significantly higher in males with p b 0.0001 (Wilcoxon test) but decreased faster (p = 0.0121). IGFBP3 was statistically significantly higher in females with p = 0.0004 (Wilcoxon test) but decreased faster (p b 0.0001). IGF1/IGFBP3 was statistically significantly higher in males with p b 0.0001 (Wilcoxon test) but decreased faster (p b 0.0001). Conclusion: Authors recommend using of a linear regression model based reference ranges for IGF1, IGFBP3 and IGF1/IGFBP3 ratio and using different reference ranges for genders. © 2015 Elsevier B.V. All rights reserved.

1. Introduction IGF1 is responsible for regulation of growth, metabolism, and differentiation of human cells. IGFBP3 is the most abundant of the carrier ⁎ Corresponding author at: Laboratory of Immunoanalysis, Department of Nuclear Medicine, Faculty Hospital Pilsen, Dr. E. Benese 13, CZ-305 99 Pilsen, Czech Republic. E-mail address: [email protected] (R. Kucera).

http://dx.doi.org/10.1016/j.cca.2015.02.036 0009-8981/© 2015 Elsevier B.V. All rights reserved.

proteins for IGF1in the blood [1]. Levels of both IGF1 and IGFBP3 decrease with age. Serum levels of IGF1 and IGFBP3 are commonly used for monitoring growth hormone (GH) production in children and adults with growth disorders [2,3]. Several studies have also related IGF1 serum levels with risk for certain malignant tumors [4] as well as for various other clinical disorders. [5–8]. We investigated the relationship between IGF1 and IGFBP3 serum levels and at the same time looked at the potential of the IGF1/IGFBP3

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IGFBP3 serum levels were measured using radioimmunoassay kit IRMA IGFBP3 (Immunotech, Prague, Czech Republic), with interassay CVs of 6.23% at a concentration of 61.5 ng/mL, and analytical sensitivity of 0.27 ng/mL. We calculated the IGF1/IGFBP3 molar ratio based on the following: 1 ng/ml IGF1 = 0.130 nmol IGF1 and 1 ng/ml IGFBP3 = 0.036 nmol IGFBP3 [9].

molar ratio as an indicator of IGF1 bioavailability [7]. Finally, we created a file of reference ranges of IGF1, IGFBP3 and IGF1/IGFBPP3 ratio for the adult population across the age spectrum. 2. Methods 2.1. Group of patients We examined a group of 1022 subjects (467 males and 555 females) between the ages of 20 to 98 years old. The group consisted of blood donors and patients undergoing regular preventive examinations. The following groups of patients were excluded from the study: patients with diabetes, high blood glucose, or high insulin levels, patients after surgery, polymorbid patients, people with oncological diseases, with renal diseases, liver diseases, diabetes mellitus, diseases of the pituitary gland and subjects using any medications that interfere in IGF1 analyses (contraceptive drugs, estrogens, corticosteroids). We divided the adult subjects into seven groups according to agegroups: 20-29, 30-39, 40-49, 50-59, 60-69, 70-79, and 80+ years, and sex. We evaluated the changes in the levels of observed analytes and the changes in IGF1/IGFBP3 ratio in each decade across the age spectrum.

2.4. Statistical analysis Quantitative variables are reported as medians, mean, Q1, Q3, 2.5th–97.5th percentiles, minimum and maximum. Age-interval-specific reference intervals for all parameters were calculated as 2.5th–97.5th percentiles. Different statistical approaches were tested. The calculated 2.5th–97.5th percentiles were plotted by cubic splines, and gender-specific curves were generated. Different statistical approaches were tested. First, a linear regression model with age as independent variable fitted by gender was calculated [10]. Second, a non-paramateric model of reference interval curves (medians and 2.5th–97.5th percentiles) for IGF1, IGFBP3, IGF1/IGFBP3 ratio as function of age by gender was calculated [11]. All medians and 2.5th–97.5th percentiles were plotted by cubic splines. Linear regression models with age as independent variable fitted by gender appeared to be the more robust model with similar results as non-parametric approach and the parametric method described by Wright and Royston, where basic transformations of the data and multiple regression techniques are combined. All statistical analyses were carried out with SAS 9.3 (Statistical Analysis Software release 9.2; SAS Institute Inc., Cary, NC, USA).

2.2. Serum samples Samples of venous blood were collected using the VACUETTE blood collection system (Greiner Bio-one Company, Kremsmünster, Austria). The separation of red blood cells was done till 2 h after collection. Blood was centrifuged for 10 min at 1700 g. Serum samples were immediately frozen at –80°C. Samples were thawed only once, just prior to analyses.

3. Results We performed the calculation of reference values of IGF1, IGFBP3 and IGF1/IGFBP3 ratio for men (Table 1), women (Table 2), separately and for the whole population (Table 3). Then we focused on the analysis of differences between male and female ranges. All three parameters IGF1, IGFBP3 and IGF1/IGFBP3 decreased with age with p b 0.0001, r = −0.64, −0.35 and −0.54, respectively. The dynamics of the decline was different between males and females.

2.3. Sample analysis We measured IGF1 serum levels using radioimmunoassay kit IRMA IGF1 (Immunotech, Marseille, France), with interassay CV of 6.8% at a concentration of 25.0 ng/mL, and analytical sensitivity of 2.0 ng/mL. The calibrators in the Immunotech IGF1 assay are calibrated against the international reference standard, WHO 87/518. Table 1 IGF1, IGFBP3 and IGF1/IGFBP3 ratio in males. Age category

N

IGF1 in males 20–29 30–39 40–49 50–59 60–69 70–79 80+

52 62 67 95 75 66 50

IGFBP3 in males 20–29 30–39 40–49 50–59 60–69 70–79 80+

52 62 67 95 75 66 50

Mean 242.37 202.65 167.66 160.82 143.55 110.15 96.18

2879.4 2688.7 2590.2 2547.7 2520.1 2492.9 2499.3

IGF1/IGFBP3 molar ratio in males 20–29 52 0.02418 30–39 62 0.02147 40–49 67 0.01815 50–59 95 0.01785 60–69 75 0.01671 70–79 66 0.01296 80+ 50 0.01133

Minimum 84.43 100.40 75.25 46.60 37.42 19.70 11.20

1887.5 1238.0 1711.0 1816.0 1204.5 1063.5 1401.0

0.00877 0.01155 0.00907 0.01019 0.00573 0.00376 0.00242

2.5th percentile 100.80 101.90 103.70 77.14 39.30 33.85 39.50

1922.0 1927.0 1966.5 1863.0 1572.0 1631.5 1425.0

0.01389 0.01508 0.00912 0.01108 0.00673 0.00416 0.00388

Lower quartile 202.10 164.60 140.00 132.60 105.60 67.70 65.80

2510.5 2440.0 2340.0 2288.5 2097.5 1959.0 1893.0

0.01910 0.01730 0.01591 0.01426 0.01308 0.00691 0.00775

Median 239.70 192.15 163.60 155.83 145.40 101.50 99.30

2838.8 2651.0 2585.5 2515.0 2474.0 2433.8 2356.3

0.02378 0.02115 0.01725 0.01751 0.01626 0.01219 0.01098

Upper quartile 282.60 242.70 188.40 183.20 182.70 147.70 126.00

3096.5 2879.5 2769.5 2723.5 3015.0 2867.5 3001.0

0.02939 0.02414 0.02110 0.02050 0.01974 0.01689 0.01355

97.5th percentile 400.00 341.21 264.90 296.60 241.20 219.60 150.00

3959.0 3967.5 3486.0 3514.0 3423.5 3812.0 4570.5

0.03546 0.03407 0.02778 0.02645 0.02973 0.02568 0.02157

Maximum 403.10 341.50 268.30 339.30 264.60 290.10 185.30

4621.0 4142.0 3545.0 3580.5 3802.0 3828.5 4570.5

0.03992 0.04077 0.02963 0.02908 0.03018 0.02935 0.02603

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Table 2 IGF1, IGFBP3 and IGF1/IGFBP3 ratio in females. Age category

N

IGF1 in females 20–29 30–39 40–49 50–59 60–69 70–79 80+

53 58 64 79 75 129 97

IGFBP3 in females 20–29 53 30–39 58 40–49 64 50–59 79 60–69 75 70–79 129 80+ 97

Mean

Minimum

188.02 167.67 150.55 135.78 134.46 83.55 74.12

3109.8 3025.4 3044.5 2970.0 2826.2 2513.6 2109.8

45.26 71.00 61.07 27.03 29.97 15.20 13.30

2334.0 1674.0 1851.0 1379.0 2073.0 758.5 775.0

IGF1/IGFBP3 molar ratio in females 20–29 53 0.01674 30–39 58 0.01575 40–49 64 0.01379 50–59 79 0.01362 60–69 75 0.01365 70–79 129 0.00934 80+ 97 0.00965

0.00442 0.00738 0.00548 0.00517 0.00355 0.00167 0.00286

2.5th percentile 80.03 84.72 66.88 54.00 57.80 16.30 15.77

2353.5 1961.5 2245.5 1680.5 2135.8 875.5 1082.5

Lower quartile 143.80 131.20 128.40 96.49 96.00 52.90 39.30

2833.5 2757.5 2700.0 2631.0 2449.3 1952.8 1520.5

0.00727 0.00754 0.00720 0.00749 0.00452 0.00247 0.00310

Median 186.10 161.10 149.18 133.90 130.30 76.40 69.30

3043.5 3025.5 3020.0 3014.5 2815.5 2531.0 2076.0

0.01280 0.01181 0.01123 0.01024 0.00946 0.00578 0.00623

0.01665 0.01455 0.01319 0.01325 0.01427 0.00876 0.00870

Upper quartile 211.30 200.40 167.70 162.10 164.00 112.50 99.40

3442.0 3348.5 3323.0 3264.0 3145.5 2981.8 2572.5

0.01960 0.01935 0.01562 0.01690 0.01635 0.01146 0.01272

97.5th percentile 359.70 281.00 277.40 249.20 250.90 175.80 170.00

3904.0 3862.5 3910.5 3849.0 3864.5 4105.5 3736.0

0.02726 0.02822 0.02336 0.02221 0.02348 0.02295 0.01812

Maximum 416.00 315.90 299.50 258.20 283.30 315.30 298.10

4332.5 4148.5 4051.0 4085.5 3875.5 6760.0 4341.5

0.03122 0.03218 0.02658 0.02544 0.02359 0.04531 0.03249

Contrary IGFBP3 was statistically significantly higher in females with p = 0.0004 (Wilcoxon test) but also decreased faster (p b 0.0001). Based on the above mentioned data, it is assumed that IGF1/IGFBP3 was statistically significantly higher in males with p b 0.0001(Wilcoxon test) but also decreased faster (p b 0.0001). Linear regression model with age as independent variable fitted by gender appeared to be a robust model with similar results as nonparametric and the parametric method described by Wright and Royston [10].

Different statistical approaches were tested. Linear regression models with age as independent variable fitted by gender are displayed in Fig. 1. Non-parametric reference interval curves (medians and 2.5th– 97.5th percentiles) for IGF1, IGFBP3 and IGF1/IGFBP3 ratio as function of age by gender are displayed in Fig. 2(a, b, c). All medians and 2.5th– 97.5th percentiles were plotted by cubic splines. For males, linear regression models were as follows: IGF1 = 291.34619 − 2.41211 × age, IGFBP3 = 2931.62778 − 6.11659 × age, IGF1/IGFBP3 = 0.02897 − 0.00021213 × age. For females, we obtained the following models: IGF1 = 241.67406 − 1.98466 × age, IGFBP3 = 3688.60561 − 16.39560 × age, IGF1/IGFBP3 = 0.02029 − 0.00013233 × age. IGF1 was statistically significantly higher in males with p b 0.0001 (Wilcoxon test) but also decreased faster (p = 0.0121).

4. Discussion Since this time many papers studying the relationship between the values, age, gender and geographical location have been published.

Table 3 IGF1, IGFBP3 and IGF1/IGFBP3 ratio in the whole population. Age category

N

Mean

IGF1 in the whole population 20–29 105 30–39 120 40–49 131 50–59 174 60–69 150 70–79 195 80+ 147

Minimum

214.93 185.74 159.30 149.45 139.00 92.55 81.62

IGFBP3 in the whole population 20–29 105 2995.7 30–39 120 2858.7 40–49 131 2819.6 50–59 174 2776.3 60–69 150 2656.2 70–79 195 2507.2 80+ 147 2242.6

45.26 71.00 61.07 27.03 29.97 15.20 11.20

1887.5 1238.0 1711.0 1379.0 1204.5 758.5 775.0

IGF1/IGFBP3 molar ratio in the whole population 20–29 105 0.02042 30–39 120 0.01858 40–49 131 0.01595 50–59 174 0.01556 60–69 150 0.01535 70–79 195 0.01046 80+ 147 0.01022

0.00442 0.00738 0.00548 0.00517 0.00355 0.00167 0.00242

2.5th percentile 84.43 90.10 75.94 61.40 49.20 19.70 15.77

2110.5 1927.0 1966.5 1816.0 1733.5 941.5 1088.5

0.00740 0.00887 0.00766 0.00757 0.00573 0.00262 0.00310

Lower quartile 172.10 144.47 132.80 115.30 101.80 55.60 46.30

2734.5 2573.5 2461.5 2448.5 2262.0 1959.0 1672.0

0.01549 0.01454 0.01268 0.01232 0.01161 0.00612 0.00720

Median 207.40 181.85 155.50 148.15 139.55 83.90 74.60

2962.5 2820.5 2755.5 2713.0 2650.3 2465.8 2178.0

0.01919 0.01799 0.01562 0.01546 0.01501 0.00938 0.00937

Upper quartile 253.60 223.10 179.80 172.60 171.10 119.50 108.90

3291.5 3207.0 3188.5 3115.0 3033.0 2932.0 2680.0

0.02518 0.02263 0.01934 0.01879 0.01888 0.01289 0.01289

97.5th percentile 400.00 312.50 268.30 263.95 241.20 199.10 170.00

3959.0 3967.5 3828.0 3731.5 3831.0 4068.0 3913.5

0.03439 0.03218 0.02710 0.02544 0.02876 0.02500 0.02157

Maximum 416.00 341.50 299.50 339.30 283.30 315.30 298.10

4621.0 4148.5 4051.0 4085.5 3875.5 6760.0 4570.5

0.03992 0.04077 0.02963 0.02908 0.03018 0.04531 0.03249

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Fig. 1. Linear regression plots by gender of IGF1, IGFBP3 and IGF1/IGFBP3 ratio.

Reference ranges as function of age and gender are very important for interpretation of IGF1 and IGFBP3 results. It is generally known that the establishment of the reference values in representative populations by considering age is the better accepted practice [12,13]. Not long ago, only radioisotope methods were used for IGF1 and IGFBP3 assessment. Only few papers related particularly to reference values have been published [14,15]. Reference values are often connected with comparing different methods [16,17]. The relation of IGF1 levels and age has been often discussed. Some current studies present very small groups of persons (between 15 and 200 individuals) and state the relation to age but only generally [18]. Other studies show that IGF1 levels decrease continuously from puberty up to the age of 50 to 60 years [19]. In our study, we have proved the decrease of IFG1 even in the

age of 80 years, comparing with persons between 70 and 80 years. As new chemiluminescence automatic methods have been introduced into the clinical routine practice many new studies comparing the different methods and different reference ranges have appeared. Besides the large number of new studies, the sizes of study groups have been also extended. Leite et al. [20,21] in their studies from 2011 to 2012 present very detailed results of reference values in Brasilian population. Authors comment reference values in relation to geographical locality, ethnic groups, age, and sex. In the study, the results of chemiluminescent and isotope methods differ not only in absolute values but also because of sex difference was relevant only for chemiluminescent method, so the problem is in using different methods, not by sex.

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a

Males

Females

b

Males

Females

c

Males

Females

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Fig. 2. (a) Non‐parametric approach by gender of IGF1, IGFBP3 and IGF1/IGFBP3 ratio. (b) Non‐parametric approach by gender of IGF1, IGFBP3 and IGF1/IGFBP3 ratio. (c) Non‐parametric approach by gender of IGF1, IGFBP3 and IGF1/IGFBP3 ratio.

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We measured IGF1, IGFBP3 and calculated IGF1/IGFBP3 ratio in 1022 persons (467 males, 555 females). IGF1 and IGFBP3 values were done by isotope method, and the values of IGF1, IGFBP3 and IGF1/IGFBP3 were significantly different in both sexes. Similar results age and gender dependence was described in Friedrich et al. [22] based on the sample of 2499 males and females. Two Turkish studies recommend the same reference interval for males and females, as we have stated [23,24]. Currently, a multicentric study based on 14970 Healthy persons was published in January 2014. Authors recommend age- and sex-adjusted reference ranges for IGF1, IGFBP3 and IGF1/IGFBP3 molar ratio [25]. IGF1 and IGFBP3 levels are regulated and influenced by multiple factors. The most frequent are genetic factors, nutritional status and different hormone production, for example, cortisol, thyroxine and sex hormones [26]. The role of growth factors in the development of different type of cancers (e.g., colorectal cancer, prostate cancer, breast cancer, melanomas) has been recently discussed [27,28]. Thus, with increasing age, it is very difficult to find healthy probands, which could be included in the study. The selection criteria for the right probands have to be applied very carefully. These factors must be taken into consideration, when reference ranges are to be established. IGF1 and IGFBP3 levels are influenced by many factors therefore; to obtain relevant results, it is necessary to establish the right selective criteria [29]. In our case, all information was obtained directly from the medical histories in the subjects' clinical charts. All patients with diabetes mellitus, renal diseases, diseases of the pituitary gland, benign and malignant tumors and liver diseases were excluded from the study. The next question before the statistical evaluation is the width of the age interval. In the literature, reference values for the adult population were divided into groups at 5-year intervals [30] or 10-year intervals [16]. Based on our results, we decided to divide the population into 10-year intervals. When we compared our results with the studies performed on the population divided into 5-year groups, we saw that the results showed similar trends. Our study seems to be beneficial due to the results of a large and very well-defined population group evaluated using robust statistical methods. According to our experience, 50 healthy persons in each age-group is the minimum number for a correct estimation of reference ranges. In some ways perhaps, the larger age range of the population is an advantage. In particular, it is possible to accumulate a larger quantity of probands in each group. Waveforms and trends in the changes of the levels of the individual parameters are gradual and depend on a number of factors, so that a greater number of probands increases the robustness of the statistical calculation. As described previously, in our study, we confirmed the fact that the values of IGF1, IGFBP3 and IGF1/IGFBP3 ratio in the total population decline with age, from ages 20 through 80+ years. When we divided the population by gender, we observed different values during the decline in age-groups of the male population and female population. For men, IGF1 decreased more steeply than in women, but the total values of IGF1 in male populations were still at a higher level than in women (Fig. 1). In the case of IGFBP3, the situation was somewhat different. Between 20 and 30 years of age, IGFBP3 is higher in women. Around the 70th year of life, the level of IGFBP3 in women in our study declined to levels less than the levels of IGFBP3 in men. Levels of IGFBP3 in men showed very gradual decline throughout the age spectrum (Fig. 1). Levels of IGF1/IGFBP3 ratio showed a similar trend as levels of IGF1 (Fig. 1). Linear regression models with age as independent variable fitted by gender seems to be the more robust model with similar results as nonparametric approach and the parametric method described by Wright and Royston [10], where basic transformations of the data and multiple regression techniques are combined to model the mean, standard deviation and skewness, and age-specific reference intervals are obtained. The age effect on concentrations of IGF1, IGFBP3 and IGF1/IGFBPP3 ratio seems to be linear. Non-parametric approach requires larger sample sizes than an estimation of reference ranges based on parametric

linear regression models with age as independent variable fitted by gender. The small advantage of a non-parametric approach is a better modeling of different variability depending on age. However, this heterogeneous variability dependent on age may be just a random effect and their statistical significance was not proven. 5. Conclusion This study established age- and sex-specific reference values for serum IGF1, IGFBP3 levels and IGF1/IGFBP3 ratio in healthy Czech adults in decades from 20 to 80 and more years of age, separately by gender. In adults, IGF1 and IGFBP3 levels and IGF1/IGFBP3 ratio decrease with age. Authors recommend using linear regression model based reference ranges for IGF1, IGFBP3 and IGF1/IGFBP3 and using different reference ranges for age and genders. Acknowledgements This study was supported by the Ministry of Health, Czech Republic, conceptual development of research organization (Faculty Hospital in Pilsen—FNPl, 00669806). References [1] Dupont J, LeRoith D. Insulin and insulin-like growth factor I receptors: similarities and differences in signal transduction. Horm Res 2001;55:22–6. [2] Bang P. Principles of growth hormone and insulin-like growth factor-I reatment in children with idiopathic short stature. Horm Res Paediatr 2011;76(Suppl. 3):24–6. [3] Clemmons DR. Value of insulin-like growth factor system markers in the assessment of growth hormone status. Endocrinol Metab Clin North Am 2007;36:109–29. [4] Samani AA, Yakar S, LeRoith D, Brodt P. The role of the IGF system in cancer growth and metastasis: overview and recent insights. Review Endocr Rev 2007;28:20–47. [5] Torres-Alemán. Insulin-like growth factor-1 and central neurodegenerative diseases. Endocrinol Metab Clin North Am 2012;41:395–408. [6] Friedrich N, Schneider H, Dörr M, et al. All-cause mortality and serum insulin-like growth factor I in primary care patients. Growth Horm IGF Res 2011;21:102–6. [7] Krassas GE, Papadopoulou P, Koliakos G, Konstantinidis T, Kalothetou K. Growth hormone, insulin growth factor-1, and igf binding protein-3 axis relationship with bone mineral density among healthy men. Arch Androl 2003;49:191–9. [8] Tian D, Kreeger PK. Analysis of the quantitative balance between insulin-like growth factor (IGF)-1 ligand, receptor, and binding protein levels to predict cell sensitivity and therapeutic efficacy. BMC Syst Biol 2014;8:98. [9] Clemmons DR. Consensus statement on the standardization and evaluation of growth hormone and insulin-like growth factor assays. Clin Chem 2011;57:555–9. [10] Wright EM, Royston P. Simplified estimation of age-specific reference interval for skewed data. Stat Med 1997;16:2785–803. [11] Lofqvist C, Andersson E, Gelander L, et al. Reference values for insulin-like growth factor-binding protein-3 (IGFBP-3) and the ratio of insulin-like growth factor-I to IGFBP-3 throughout childhood and adolescence. J Clin Endocrinol Metab 2005;90: 1420–7. [12] Quarmby V, Quan C, Ling V, Compton P, Canova-Davis E. How much insulin-like growth factor I (IGF-I) circulates? Impact of standardization on IGF-I assay accuracy. J Clin Endocrinol Metab 1998;83:1211–6. [13] Hjortebjerg R, Frystyk J. Determination of IGFs and their binding proteins. Best Pract Res Clin Endocrinol Metab 2013;27:771–81. [14] Ranke MB, Osterziel KJ, Schweizer R, et al. Reference levels of insulin-like growth factor I in the serum of healthy adults: comparison of four immunoassays. Clin Chem Lab Med 2003;41:1329–34. [15] Barkan AL. Defining normalcy of the somatotropic axis: an attainable goal? Pituitary 2007;10:135–9. [16] Massart C, Poirier JY. Serum insulin-like growth factor-I measurement in the followup of treated acromegaly: comparison of four immunoassays. Clin Chim Acta 2006; 373:176–9. [17] Elmlinger MW, Kühnel W, Weber MM, Ranke MB. Reference ranges for two automated chemiluminescent assays for serum insulin-like growth factor I (IGF-I) and IGF-binding protein 3 (IGFBP-3). Clin Chem Lab Med 2004;42:654–64. [18] Lin CM, Huang YL, Lin ZY. Influence of gender on serum growth hormone, insulinlike growth factor-I and its binding protein-3 during aging. Yonsei Med J 2009;50: 407–13. [19] Aimaretti G, Boschetti M, Corneli G, et al. Normal age-dependent values of serum insulin growth factor-I: results from a healthy Italian population. J Endocrinol Invest 2008;31:445–9. [20] Leite DB, Meirelles RM, Mandarim-de-Lacerda CA, Matos HJ, Bernardo-Filho M. Serum insulin-like growth factor-I adult reference values for an automated chemiluminescence immunoassay system. Afr J Biotechnol 2011;10:18027–33. [21] Leite DB, Meirelles RM, Mandarim-De-Lacerda CA, Matos HJ, Santos-Filho SD, Bernardo-Filho M. Determination of insulin-like growth factor-I reference values using an immunoradiometric assay in a Brazilian adult population. Indian J Med Sci 2012;66:155–63.

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