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DOI: 10.1055/s00431768951
Martin's Formula As the Most Suitable Method for Estimation of LowDensity Lipoprotein Cholesterol in Indian Population
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusion
 Limitation of Study
 References
Abstract
Background Because of cost effectiveness, most of the laboratories in India estimate lowdensity lipoprotein cholesterol (LDLC) levels with the Friedewald's formula. There were many shortcomings of the Friedewald's formula. Recently, Martin and colleagues have derived a new formula for calculating LDLC. The present study was undertaken to calculate LDLC using various formulae (Friedewald's formula, Anandaraja's formula, and Martin's formula) and to compare directly measured LDLC (DLDLC) with calculated LDLC at various ranges of triglyceride (TG) concentration.
Materials and Methods The present study compared LDLC measured by Martin's formula, Friedewald's formula, and Anandaraja's formula with DLDLC in 280 outpatient fasting samples between the age groups of 18 and 50 years. Depending on the TG values, study samples were divided into four groups. Group 1: less than 200 mg/dL; Group 2: 200 to 300 mg/dL; Group 3: 300 to 400 mg/dL; and Group 4: more than 400 mg/dL.
Results Martin's formula shows highest correlation with rvalue of 0.9979 compared with Friedewald's (0.9857) and Anandaraja's (0.9683) rvalues. The mean difference was least for Martin's formula (0.31 ± 3.53) compared with other formulae. Among all the groups, percentage of error was least for Martin's formula (0.23%). Martin's LDLC shows highest concordance (90.90%) compared with Friedewald's (79.60%) and Anandaraja's formulae (82.90%).
Conclusion Among all the groups, Martin's formula shows highest correlation, least percentage of error, highest concordance, and least mean differences. At all TG levels, Martin's formula is the best formula compared with the Friedewald's formula and Anandaraja's formula.
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Introduction
The National Cholesterol Education Program Adult Treatment Panel III (NCEPATP III) guidelines suggest to start the drug therapy if lowdensity lipoprotein cholesterol (LDLC) levels are more than 130 mg/dL. This makes accurate reporting of LDLC crucial in the management of dyslipidemia patients.[1] Ultracentrifugation and βquantitation are the gold standard methods for LDLC measurement. Other methods include direct measurement of LDLC using a homogenous assay. These methods are expensive, inconvenient, and not readily available in most of the routine laboratories.[2] Because of these limitation, many clinical laboratories throughout the world use a less expensive and easy approach for the estimation of LDLC, that is, Friedewald's formula.[3] However, there are several shortcomings of this formula, mainly the underestimation of LDLC at high triglyceride (TG) levels and overestimation at low TG levels.[4] Many attempts have been made to evaluate and refine Friedewald's formula. The different modified formulae like Anandaraja's formula[5] and Martin's formula[6] have been developed. Compared with Friedewald's formula, Aanandaraja's formula[5] uses only two analytes, TG and total cholesterol (TC), for calculation, which may decrease the total error when compared with the Friedewald's formula.
Friedewald's equation uses a fixed value equal to 5 as a divisor for TG; it does not account for interindividual variability, often resulting in underestimation of risk and potential under treatment.[7] In contrast, Martin et al[7] provided a new formula by introducing adjustable factor in the formula. Martin's formula is: (TC–highdensity lipoprotein cholesterol [HDLC]) – (TGs/adjustable factor).[7] Adjustable factor, defined by levels of TG and nonHDLC, is divisor for TG. This adjustable factor ranges from 3.1 to 11.9 and was derived from an analysis of TGtoverylowdensity lipoprotein (VLDL)C ratios of more than 1.3 million people.[7] There are few studies reporting use of this formula in India.
Accurately determining LDLC values is important in clinical laboratory practice because LDLC is employed to manage patients having a high risk of coronary heart disease. Therefore, most alternative formulae have been developed to estimate LDLC to be appropriate for ethnic, specific, as well as other populations. The present study was undertaken with the aim to determine which of these calculated formulas (Friedewald's, Anandaraja's, and Martin's formulas) shows maximum correlation with directly measured LDLC (DLDLC) at different serum TG levels.
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Materials and Methods
Study Design
This study is an observational study. Study samples were collected from KLE Centenary Charitable Hospital and Medical Research Center, Belgaum. Total 280 outpatient fasting complete lipid profile patients of 18 to 50 years of age were included in the study. Ethical clearance was obtained from institution ethics committee USM KLE International Medical Program Belgavi: Ethical approval number USMKLE/IEC/04–2020.Written informed consent was taken from all participants.
Inclusion criteria: 280 outpatient fasting samples coming to laboratory for lipid profile; age group, 18 to 50 years.
Exclusion criteria: Patients with diabetes mellitus, hypothyroidism, cirrhosis, chronic hepatitis, chronic kidney disease, pancreatitis, and patients on active medication including steroids, statins, and omega3 fatty acids were excluded from the study
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Calculation of Sample Size
Direct method LDLC mean = 118.02[8]
Friedewald method mean = 107.22[8]
Standard deviation in direct method = 35.45
Standard deviation in Friedewald method = 24.35
Effect size: 0.261538461538461
Power = 95%
Alpha error = 1%
Required sample size = 266 should be taken
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Sample Collection and Lipoprotein Analysis
As a routine procedure, the samples were collected after 10 to 12 hours of overnight fasting by withdrawing 3 mL of venous blood in plain vial. The samples were centrifuged at 3,000 rpm for 15 minutes to obtain serum and were analyzed for lipid profile on the same day. The serum lipid profile parameters were total cholesterol, TG, HDLC, and LDLC, which were analyzed on EM 360 clinical chemistry analyzer (TransAsia BioMedicals Ltd, Mumbai, Maharashtra, India). All the lipid parameters were estimated using kits purchased from Erba Mannheim XL system packs. The linearity (intraassay) coefficients of TC, TG, HDLC, and LDLC assays were 4.2 to 695 mg/dL (0.98–1.21%), 9.74 to 1,062 mg/dL (0.48–0.86%), 1.90 to 193 mg/dL (1.32–1.95%), and 2.60 to 263 mg/dL (1.74–2.16%), respectively. The intraassay coefficients observed in our analysis were in concurrence with manufacturer's measurements. All quality controls were performed to ensure the accuracy of the analytical testing (internal and external controls). The internal control is routinely processed every 24 hours on two levels (normal and pathological) by Liquichek Lipids Control from BioRad laboratories, Inc. The results are analyzed daily and periodically for the evaluation of the Levey Jennings graph. The laboratory's external quality control is performed every 3 months. All the lipid parameters' assays meet the National Institutes of HealthNCEP goals for acceptable performance (LDLCV <4%, Bias <4%and Total Error of <12%, for HDLCV<4%,Bias ≤ ± 5% and total error ≤13%, for TCCV<3%,Bias ≤ ± 3% and total error ≤8.9%, for TGCV<5%,Bias ≤ ± 5% and total error ≤15%,).
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LDL Cholesterol Was Calculated by following Formulae

Friedewald's formula[4] (FLDLC) = TC − (TG/5 + HDLC)

Anandaraja's formula[5] (ALDLC) = (0.9 × TC) − (0.9 × TG/5) – 28

Martin's formula[6] (MLDLC) = (TCHDLC) – (TG/adjustable factor*)
*Adjustable factor: The adjustable factor is based on TG and nonHDLC concentrations. Martin's method matches each person with 1 of 180 different factors to estimate VLDLC cholesterol from TGs. Martin's LDLC was calculated using an LDLC calculator (htttp://www.ldlcalculator.com). Copy the values for total cholesterol, HDLC, and TGs from research database into the Excel file: nonHDLC, the adjustable factor, and LDLC by Martin's formula will be automatically calculated. Depending on the TG values, study samples were divided into four groups:
Group 1: less than 200 mg/dL
Group 2: 200 to 300 mg/dL
Group 3: 300 to 400 mg/dL
Group 4: more than 400 mg/dL
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Statistical Analysis
The data obtained were entered into Microsoft Excel sheet and statistical analysis was performed with the SPSS version 16.0. Paired ttest and Pearson's correlation were performed to find the significant difference and correlation between DLDLC and calculated LDL by different formulas. Scatter plot was used to represent the correlation between the two methods. The mean percentage of error was calculated using the formula: (calculated LDLC − DLDLC)/DLDLC × 100. pValue less than 0.05 is considered as significant.
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Results
The study consists of total 280 samples. Depending on the TG values (66–533 mg/dL), study population was divided into four groups. There were 124 participants in Group 1, 91 participants in Group 2, 36 participants in Group 3, and 29 participants in Group 4.
[Table 1] shows the baseline characteristics of the study population, like gender and sex. Comparison of gender and age between groups is statistically not significant. There was no significant difference in age and gender in study population between groups ([Table1]).
Abbreviation: SD, standard deviation.
Note: p < 0.05 is statistically significant.
LDLC was calculated according to three different formulae and compared with DLDLC ([Table 2]). Correlation coefficient r was calculated with each formula by correlation analysis of the data. The best formula was chosen in terms of the highest correlation and the lowest mean difference and standard deviation. LDLC by Martin's formula showed a highest correlation of rvalue (0.9979), compared with Friedewald's (0.9857) and Anandaraja's (0.9683) formulas ([Table 2]; [Fig. 1]).
Abbreviation: LDLC, lowdensity lipoprotein cholesterol.
Note: r = correlation coefficient; p < 0.05 is statistically significant.
Comparison of mean of DLDLC with calculated LDLC ([Table 3]) by Friedewald's formula and Anandaraja's formula shows that it is underestimated at all levels of TG, and it is statistically significant. Among total sample, mean difference of direct and calculated formulas was least for Martin's formula (0.31 ± 3.53) compared with other formulae. In Group 1, mean difference was least for Anandaraja's formula (1.08 ± 8.35) compared with other formulae. In Groups 2, 3, and 4, mean difference was least for Martin's formula with values 0.65 ± 5.17, 0.00 ± 2.47, and 0.77 ± 5.13, respectively, compared with other formulae.
Abbreviations: LDLC, lowdensity lipoprotein cholesterol; SD, standard deviation.
Note: Mean difference = direct LDL cholesterol – formulacalculated LDL cholesterol; p < 0.05 is statistically significant.
Percentage of error from DLDLC and calculated LDLC was least for Martin's formula ([Table 4]; [Fig. 1]) in total study sample and in all groups compared with other formulae.
Abbreviation: LDLC, lowdensity lipoprotein cholesterol.
Note: Percentage of error = (Calculated LDL cholesterol – Direct LDL cholesterol)/Direct LDLC × 100.
The present study compared the concordance of the DLDLC with the estimated LDLC when classifying LDLC values by NCEPATP III. We labeled the result as being “concordant” if the two values were in the same classification, as an “overestimation” if the estimated value was greater than the direct measurement, or as an “underestimation” if the estimated value was less than the direct measurement.
Martin's formula (90.90%) resulted in the best concordance with the direct measurement compared with Friedewald's formula (79.60%) and Anandaraja's formula (82.90%). Overestimation and underestimation rates produced by Martin's formula are less than those produced by Friedewald's and Anandaraja's formulas.
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Discussion
The underestimation of LDLC will lead to delay in initiation of treatment to patients who are at high risk of dyslipidemia. Meanwhile, overestimation can also lead to exposure of patients to unnecessary drug therapy. So there is a need to find an accurate equation for estimation of LDLC with the best performance comparable to the DLDLC. Since Friedewald's formula has limitations, many attempts have been made to derive more accurate formula for LDLC calculation. The present study was undertaken with the aim to determine which of these calculated formulae (Friedewald's, Anandaraja's and Martin's formula) shows maximum correlation with DLDLC at different serum TG levels.
Previous studies like Sahu et al[9] and Molavi et al[10] have shown that the Friedewald's equation performs better for certain groups of populations. But in the study we found calculated LDLC is underestimated in all the groups. Among all the formulas, mean difference and percentage of error produced by Friedewald's equation are high in total sample and in Groups 2, 3, and 4. The results are consistent with the results previously reported by Kamal et al,[11] Agrawal et al,[12] and Tremblay et al,[13] which shows that Friedewald's formula underestimates LDLC at higher TG ranges. It may be because the performance of Friedewald's equation steadily decreases with increasing TG and is not recommended for hypertriglyceride (<400 mg/dL) ranges. In contradictory studies, Mora et al[14] and Gazi and Elisaf[15] have reported overestimation of LDLC by Friedewald's formula as compared with DLDLC.
The present study shows underestimation by Anandaraja's formula compared with the DLDLC. Previous studies conducted by Kapoor et al,[8] Kamal et al,[11] Gupta et al,[16] Kamezaki et al,[17] and Sudha et al[18] also reported underestimation by Anandaraja's formula. In Group 1, mean difference between Anandaraja's formula and DLDLC is least compared with other formulas. The results are consistent with Krishnaveni and Gowda.[19] Krishnaveni and Gowda[19] showed that for subjects with serum TG levels less than 100 mg/dL, Anandaraja's formula was the most accurate.
Kamal et al,[11] Miller et al,[20] and Nakanishi et al[21] have showed that as TG levels increase, there is an increase in mean difference between direct and formulacalculated LDLC. The present study results support this finding: with an increase in TG concentrations, the difference between DLDLC and LDLC calculated by Friedewald's and Anandaraja's formulas increased. Gupta et al.[16] and Lee et al[22] observed that LDLC concentrations had no relation with TG concentrations. MartinLDLC values were closer to DLDLC in all the groups.
Martin's formula (90.90%) resulted in the best concordance with the direct measurement compared with Friedewald's formula (79.60%) and Anandaraja's formula (82.90%). The results are consistent with studies done by Martin et al,[7] Kang et al,[6] and Lee et al.[22] Overestimation and underestimation rates produced by Martin's formula are less than those produced by Friedewald's and Anandaraja's formulas; the difference is particularly pronounced in the underestimation rate. This is of particular importance because underestimation is generally considered riskier than overestimation, especially when screening the general population, as underestimation can cause delays in initiation of treatment.
The present study shows tendency of the Friedewald's formula to underestimate LDLC. It is in these clinical conditions that Martin's formula may be more useful. In all the groups, Pearson's correlation coefficient rvalue was high for Martin's formula compared with Friedewald's formula. It was suggested that Martin's formula may prevent undertreatment due to the underestimation of LDLC using Friedewald's formula. Our results confirmed those of Martin et al,[7] Kang et al,[6] and Lee et al,[22] who stated that Martin's formula offers a significant improvement in LDLC estimation when compared with Friedewald's formula. Martin's formula can be used instead of routine Friedewald's formula as Martin's formula is more accurate.
In a developing country like India with a burdening population with high TG, there is a need to adopt the novel equation. Martin's 180cell approach could be coded into an online calculator, smartphone application, or automated laboratory reporting system.
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Conclusion
In the present study, Martin's formula showed high correlation, lower mean difference, highest concordance, and low percentage of errors in all the groups compared with Friedewald's formula and Anandaraja's formula. At all TG levels, Martin's formula is best compared with Friedewald's formula and Anandaraja's formula.
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Limitation of Study
This present study has a few limitations. First, the results may not be generalizable to the overall population, as there may be differences in baseline characteristics between our subjects and the general population. We had only access to the lipid profiles of the subjects and clinical characteristics or clinical outcomes of patients in our sample were unknown. Second, instead of calculating the adjustable factor for Martin's formula, we used the calculator that was suggested by the authors, and hence there is a possibility that the adjustable factor for the Indian population may be different from what Martin et al reported.
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Conflict of Interest
None declared
Funding
None.
Presentation at a Meeting
None.
Authors' Contributions
S.A. developed the concept, designed the study, and prepared the manuscript. F.F. collected the samples, analyzed the samples, and helped in manuscript editing. K.J. prepared and edited the manuscript. S.J. helped in statistical analysis of data and manuscript editing.

References
 1 Talwalkar PG, Sreenivas CG, Gulati A, Baxi H. Journey in guidelines for lipid management: from adult treatment panel (ATP)I to ATPIII and what to expect in ATPIV. Indian J Endocrinol Metab 2013; 17 (04) 628635
 2 Badrakiya KM, Shah AD, Makadia MG. Comparison of LDLcholesterol estimated by direct method and by calculation. IJBAR 2016; 7 (08) 353358
 3 Schaefer EJ, Otokozawa S, Ai M. Limitations of direct methods and the reference method for measuring HDL and LDL cholesterol. Clin Chem 2011; 57 (07) 10811083 , author reply 1083
 4 Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of lowdensity lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972; 18 (06) 499502
 5 Anandaraja S, Narang R, Godeswar R, Laksmy R, Talwar KK. Lowdensity lipoprotein cholesterol estimation by a new formula in Indian population. Int J Cardiol 2005; 102 (01) 117120
 6 Kang M, Kim J, Lee SY, Kim K, Yoon J, Ki H. Martin's equation as the most suitable method for estimation of lowdensity lipoprotein cholesterol levels in Korean adults. Korean J Fam Med 2017; 38 (05) 263269
 7 Martin SS, Blaha MJ, Elshazly MB. et al. Comparison of a novel method vs the Friedewald equation for estimating lowdensity lipoprotein cholesterol levels from the standard lipid profile. JAMA 2013; 310 (19) 20612068
 8 Kapoor R, Chakraborty M, Singh N. A leap above Friedewald formula for calculation of lowdensity lipoproteincholesterol. J Lab Physicians 2015; 7 (01) 1116
 9 Sahu S, Chawla R, Uppal B. Comparison of two methods of estimation of low density lipoprotein cholesterol, the direct versus Friedewald estimation. Indian J Clin Biochem 2005; 20 (02) 5461
 10 Molavi F, Namazi N, Asadi M. et al. Comparison common equations for LDLC calculation with direct assay and developing a novel formula in Iranian children and adolescents: the CASPIAN V study. Lipids Health Dis 2020; 19 (01) 129
 11 Kamal AH, Hossain M, Chowdhury S, Mahmud NU. A comparison of calculated with direct measurement of low density lipoprotein cholesterol level. JCMCTA 2009; 20: 1923
 12 Agrawal M, Spencer HJ, Faas FH. Method of LDL cholesterol measurement influences classification of LDL cholesterol treatment goals: clinical research study. J Investig Med 2010; 58 (08) 945949
 13 Tremblay AJ, Morrissette H, Gagné JM, Bergeron J, Gagné C, Couture P. Validation of the Friedewald formula for the determination of lowdensity lipoprotein cholesterol compared with betaquantification in a large population. Clin Biochem 2004; 37 (09) 785790
 14 Mora S, Rifai N, Buring JE, Ridker PM. Comparison of LDL cholesterol concentrations by Friedewald calculation and direct measurement in relation to cardiovascular events in 27,331 women. Clin Chem 2009; 55 (05) 888894
 15 Gazi IF, Elisaf M. LDLcholesterol calculation formulas in patients with or without the metabolic syndrome. Int J Cardiol 2007; 119 (03) 414415
 16 Gupta S, Verma M, Singh K. Does LDLC estimation using Anandaraja's formula give a better agreement with direct LDLC estimation than the Friedewald's formula?. Indian J Clin Biochem 2012; 27 (02) 127133
 17 Kamezaki F, Sonoda S, Nakata S, Otsuji Y. A direct measurement for LDLcholesterol increases hypercholesterolemia prevalence: comparison with Friedewald calculation. J UOEH 2010; 32 (03) 211220
 18 Sudha K, Prabhu A, Kiran AM, Marathe A, Hegde A. Validation of the Friedewald formula in type II diabetes mellitus: an Indian perspective study. Int J Biol Adv Res 2015; 6: 103106
 19 Krishnaveni P, Gowda VM. Assessing the validity of Friedewald's formula and Anandraja's formula for serum LDLcholesterol calculation. J Clin Diagn Res 2015; 9 (12) BC01BC04
 20 Miller WG, Myers GL, Sakurabayashi I. et al. Seven direct methods for measuring HDL and LDL cholesterol compared with ultracentrifugation reference measurement procedures. Clin Chem 2010; 56 (06) 977986
 21 Nakanishi N, Matsuo Y, Yoneka H, Nakamura K, Suzuki K, Tatara K. Validity of the conventional indirect methods including Friedewald method for determining serum low density lipoprotein cholesterol level: comparison with the direct homogenous enzymatic analysis. J Occup Health 2002; 42: 130137
 22 Lee J, Jang S, Son H. Validation of the Martin method for estimating lowdensity lipoprotein cholesterol levels in Korean adults: findings from the Korea National Health and Nutrition Examination Survey, 2009–2011. PLoS One 2016; 11 (01) e0148147
Address for correspondence
Publication History
Received: 30 July 2022
Accepted: 31 March 2023
Article published online:
13 July 2023
© 2023. The Indian Association of Laboratory Physicians. This is an open access article published by Thieme under the terms of the Creative Commons AttributionNonDerivativeNonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/byncnd/4.0/)
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References
 1 Talwalkar PG, Sreenivas CG, Gulati A, Baxi H. Journey in guidelines for lipid management: from adult treatment panel (ATP)I to ATPIII and what to expect in ATPIV. Indian J Endocrinol Metab 2013; 17 (04) 628635
 2 Badrakiya KM, Shah AD, Makadia MG. Comparison of LDLcholesterol estimated by direct method and by calculation. IJBAR 2016; 7 (08) 353358
 3 Schaefer EJ, Otokozawa S, Ai M. Limitations of direct methods and the reference method for measuring HDL and LDL cholesterol. Clin Chem 2011; 57 (07) 10811083 , author reply 1083
 4 Friedewald WT, Levy RI, Fredrickson DS. Estimation of the concentration of lowdensity lipoprotein cholesterol in plasma, without use of the preparative ultracentrifuge. Clin Chem 1972; 18 (06) 499502
 5 Anandaraja S, Narang R, Godeswar R, Laksmy R, Talwar KK. Lowdensity lipoprotein cholesterol estimation by a new formula in Indian population. Int J Cardiol 2005; 102 (01) 117120
 6 Kang M, Kim J, Lee SY, Kim K, Yoon J, Ki H. Martin's equation as the most suitable method for estimation of lowdensity lipoprotein cholesterol levels in Korean adults. Korean J Fam Med 2017; 38 (05) 263269
 7 Martin SS, Blaha MJ, Elshazly MB. et al. Comparison of a novel method vs the Friedewald equation for estimating lowdensity lipoprotein cholesterol levels from the standard lipid profile. JAMA 2013; 310 (19) 20612068
 8 Kapoor R, Chakraborty M, Singh N. A leap above Friedewald formula for calculation of lowdensity lipoproteincholesterol. J Lab Physicians 2015; 7 (01) 1116
 9 Sahu S, Chawla R, Uppal B. Comparison of two methods of estimation of low density lipoprotein cholesterol, the direct versus Friedewald estimation. Indian J Clin Biochem 2005; 20 (02) 5461
 10 Molavi F, Namazi N, Asadi M. et al. Comparison common equations for LDLC calculation with direct assay and developing a novel formula in Iranian children and adolescents: the CASPIAN V study. Lipids Health Dis 2020; 19 (01) 129
 11 Kamal AH, Hossain M, Chowdhury S, Mahmud NU. A comparison of calculated with direct measurement of low density lipoprotein cholesterol level. JCMCTA 2009; 20: 1923
 12 Agrawal M, Spencer HJ, Faas FH. Method of LDL cholesterol measurement influences classification of LDL cholesterol treatment goals: clinical research study. J Investig Med 2010; 58 (08) 945949
 13 Tremblay AJ, Morrissette H, Gagné JM, Bergeron J, Gagné C, Couture P. Validation of the Friedewald formula for the determination of lowdensity lipoprotein cholesterol compared with betaquantification in a large population. Clin Biochem 2004; 37 (09) 785790
 14 Mora S, Rifai N, Buring JE, Ridker PM. Comparison of LDL cholesterol concentrations by Friedewald calculation and direct measurement in relation to cardiovascular events in 27,331 women. Clin Chem 2009; 55 (05) 888894
 15 Gazi IF, Elisaf M. LDLcholesterol calculation formulas in patients with or without the metabolic syndrome. Int J Cardiol 2007; 119 (03) 414415
 16 Gupta S, Verma M, Singh K. Does LDLC estimation using Anandaraja's formula give a better agreement with direct LDLC estimation than the Friedewald's formula?. Indian J Clin Biochem 2012; 27 (02) 127133
 17 Kamezaki F, Sonoda S, Nakata S, Otsuji Y. A direct measurement for LDLcholesterol increases hypercholesterolemia prevalence: comparison with Friedewald calculation. J UOEH 2010; 32 (03) 211220
 18 Sudha K, Prabhu A, Kiran AM, Marathe A, Hegde A. Validation of the Friedewald formula in type II diabetes mellitus: an Indian perspective study. Int J Biol Adv Res 2015; 6: 103106
 19 Krishnaveni P, Gowda VM. Assessing the validity of Friedewald's formula and Anandraja's formula for serum LDLcholesterol calculation. J Clin Diagn Res 2015; 9 (12) BC01BC04
 20 Miller WG, Myers GL, Sakurabayashi I. et al. Seven direct methods for measuring HDL and LDL cholesterol compared with ultracentrifugation reference measurement procedures. Clin Chem 2010; 56 (06) 977986
 21 Nakanishi N, Matsuo Y, Yoneka H, Nakamura K, Suzuki K, Tatara K. Validity of the conventional indirect methods including Friedewald method for determining serum low density lipoprotein cholesterol level: comparison with the direct homogenous enzymatic analysis. J Occup Health 2002; 42: 130137
 22 Lee J, Jang S, Son H. Validation of the Martin method for estimating lowdensity lipoprotein cholesterol levels in Korean adults: findings from the Korea National Health and Nutrition Examination Survey, 2009–2011. PLoS One 2016; 11 (01) e0148147