Breast and colorectal cancer risks among over 6,000 CHEK2 pathogenic variant carriers: A comparison of missense versus truncating variants.

BACKGROUND AND AIMS: Heterozygous truncating pathogenic variants (PVs) in CHEK2 confer a 1.5 to 3-fold increased risk for breast cancer and may elevate colorectal cancer risks. Less is known regarding missense variants. Here we compared the cancer associations with truncating and missense PVs in CHEK2 across breast and colorectal cancer. METHODS: This was a retrospective analysis of 705,797 patients who received single laboratory multigene panel testing between 2013 and 2020. Multivariable logistic regression models determined cancer risk associated with CHEK2 variants as odds ratios (ORs) and 95% confidence intervals (CIs) after adjusting for age at diagnosis, cancer history, and ancestry. Breast and colorectal cancer analyses were performed using 6255 CHEK2 PVs, including truncating PVs (N = 4505) and missense PVs (N = 1750). RESULTS: CHEK2 PVs were associated with an increased risk of ductal invasive breast cancer (p < 0.001) and ductal carcinoma in situ (DCIS) (p < 0.001), with no statistically significant differences when truncating PVs (p < 0.001) and missense PVs (p < 0.001) were evaluated separately. All CHEK2 variants assessed conferred little to no risk of colorectal cancer. CONCLUSIONS: In our large cohort, CHEK2 truncating and missense PVs conferred similar risks for breast cancer and did not seem to elevate risk for colorectal cancer.

Impact of a Cancer Gene Variant Reclassification Program Over a 20-Year Period.

PURPOSE: Hereditary cancer genetic testing can inform personalized medical management for individuals at increased cancer risk. However, many variants in cancer predisposition genes are individually rare, and traditional tools may be insufficient to evaluate pathogenicity. This analysis presents data on variant classification and reclassification over a 20-year period. PATIENTS AND METHODS: This is a retrospective analysis of > 1.9 million individuals who received hereditary cancer genetic testing from a single clinical laboratory (March 1997 to December 2017). Variant classification included review of evidence from traditional tools (eg, population frequency databases, literature) and laboratory-developed tools (eg, novel statistical methods, in-house RNA analysis) by a multidisciplinary expert committee. Variants may have been reclassified more than once and with more than one line of evidence. RESULTS: In this time period, 62,842 unique variants were observed across 25 cancer predisposition genes, and 2,976 variants were reclassified. Overall, 82.1% of reclassification events were downgrades (eg, variant of uncertain significance [VUS] to benign), and 17.9% were upgrades (eg, VUS to pathogenic). Among reclassified variants, 82.8% were initially classified as VUS, and 47.5% were identified in ≤ 20 individuals (allele frequency ≤ 0.001%). Laboratory-developed tools were used in 72.3% of variant reclassification events, which affected > 600,000 individuals. More than 1.3 million patients were identified as carrying a variant that was reclassified within this 20-year time period. CONCLUSION: The variant classification program used by the laboratory evaluated here enabled the reclassification of variants that were individually rare. Laboratory-developed tools were a key component of this program and were used in the majority of reclassifications. This demonstrates the importance of using robust and novel tools to reclassify rare variants to appropriately inform personalized medical management.

Prevalence of admission plasma glucose in 'diabetes' or 'at risk' ranges in hospital emergencies with no prior diagnosis of diabetes by gender, age and ethnicity.

AIMS: To establish the prevalence of admission plasma glucose in 'diabetes' and 'at risk' ranges in emergency hospital admissions with no prior diagnosis of diabetes; characteristics of people with hyperglycaemia; and factors influencing glucose measurement. METHODS: Electronic patient records for 113 097 hospital admissions over 1 year from 2014 to 2015 included 43 201 emergencies with glucose available for 31 927 (74%) admissions, comprising 22 045 people. Data are presented for 18 965 people with no prior diagnosis of diabetes and glucose available on first attendance. RESULTS: Three quarters (14 214) were White Europeans aged 62 (43-78) years, median (IQ range); 12% (2241) South Asians 46 (32-64) years; 9% (1726) Unknown/Other ethnicities 43 (29-61) years; and 4% (784) Afro-Caribbeans 49 (33-63) years, P < .001. Overall, 5% (1003) had glucose in the 'diabetes' range (≥11.1 mmol/L) higher at 8% (175) for South Asians; 16% (3042) were 'at risk' (7.8-11.0 mmol/L), that is 17% (2379) White Europeans, 15% (338) South Asians, 14% (236) Unknown/Others and 11% (89) Afro-Caribbeans, P < .001. The prevalence for South Asians aged <30 years was 2.1% and 5.2%, respectively, 2.6% and 8.6% for Afro-Caribbeans <30 years, and 2.0% and 8.4% for White Europeans <40 years. Glucose increased with age and was more often in the 'diabetes' range for South Asians than White Europeans with South Asian men particularly affected. One third of all emergency admissions were for <24 hours with 58% of these having glucose measured compared to 82% with duration >24 hours. CONCLUSIONS: Hyperglycaemia was evident in 21% of adults admitted as an emergency; various aspects related to follow-up and initial testing, age and ethnicity need to be considered by professional bodies addressing undiagnosed diabetes in hospital admissions.

High risk of breast cancer in women with biallelic pathogenic variants in CHEK2.

PURPOSE: Compared to breast cancer risk genes such as BRCA2, ATM, PALB2, and NBN, no defined phenotype is currently associated with biallelic pathogenic variants (PVs) in CHEK2. This study compared the prevalence of breast and other cancers in women with monoallelic and biallelic CHEK2 PVs. METHODS: CHEK2 PV carriers were identified through commercial hereditary cancer panel testing (09/2013-07/2019). We compared cancer histories of 6473 monoallelic carriers to 31 biallelic carriers. Breast cancer risks were estimated using multivariate logistic regression and are reported as odds ratios (OR) with 95% confidence intervals (CI). RESULTS: Breast cancer frequency was higher among biallelic CHEK2 PV carriers (80.6%, 25/31) than monoallelic carriers (41.2%, 2668/6473; p < 0.0001). Biallelic carriers were more likely to be diagnosed at or before age 50 (61.3%, 19/31) and to have a second breast cancer diagnosis (22.6%, 7/31) compared to monoallelic carriers (23.9%, 1548/6473; p < 0.0001 and 8.1%, 523/6473; p = 0.0107, respectively). Proportionally more biallelic carriers also had any cancer diagnosis and > 1 primary diagnosis. Compared to women with no PVs, biallelic PV carriers had a higher risk of developing ductal invasive breast cancer (OR 8.69, 95% CI 3.69-20.47) and ductal carcinoma in situ (OR 4.98, 95% CI 2.00-12.35) than monoallelic carriers (OR 2.02, 95% CI 1.90-2.15 and OR 1.82, 95% CI 1.66-2.00, respectively). CONCLUSIONS: These data suggest that biallelic CHEK2 PV carriers have a higher risk for breast cancer, are more likely to be diagnosed younger, and to have multiple primary breast cancers compared to monoallelic carriers. Biallelic carriers also appear to have a higher risk of cancer overall. Therefore, more aggressive management may be appropriate for women with biallelic PVs in CHEK2 compared with current recommendations for monoallelic carriers.

A substantial proportion of apparently heterozygous TP53 pathogenic variants detected with a next-generation sequencing hereditary pan-cancer panel are acquired somatically.

Previous analysis of next-generation sequencing (NGS) hereditary pan-cancer panel testing demonstrated that approximately 40% of TP53 pathogenic and likely pathogenic variants (PVs) detected have NGS allele frequencies between 10% and 30%, indicating that they likely are acquired somatically. These are seen more frequently in older adults, suggesting that most result from normal aging-related clonal hematopoiesis. For this analysis, apparent heterozygous germline TP53 PV carriers (NGS allele frequency 30-70%) were offered follow-up testing to confirm variant origin. Ninety-eight probands had samples submitted for follow-up family member testing, fibroblast testing, or both. The apparent heterozygous germline TP53 PV was not detected in 32.6% (15/46) of submitted fibroblast samples, indicating that it was acquired somatically, either through clonal hematopoiesis or via constitutional mosaicism. Notably, no individuals with confirmed germline or likely germline TP53 PVs met classic Li-Fraumeni syndrome (LFS) criteria, only 41% met Chompret LFS criteria, and 59% met neither criteria, based upon provider-reported personal and family cancer history. Comprehensive reporting of TP53 PVs detected using NGS, combined with follow-up analysis to confirm variant origin, is advised for clinical testing laboratories. These findings underscore the investment required to provide individuals and family members with clinically accurate genetic test results pertaining to their LFS risk.

Prevalence of Variant Reclassification Following Hereditary Cancer Genetic Testing.

Importance: Variant reclassification is an important component of hereditary cancer genetic testing; however, there are few published data quantifying the prevalence of reclassification. Objective: Retrospective cohort study of individuals who had genetic testing from 2006 through 2016 at a single commercial laboratory. Design, Setting, and Participants: A retrospective cohort of individuals who had genetic testing between 2006 and 2016 at a single commercial laboratory was assessed. Variants were classified as benign, likely benign, variant of uncertain significance, likely pathogenic, or pathogenic. Retrospective chart reviews were conducted for patients from the University of Texas Southwestern (UTSW) Medical Center. Exposures: Hereditary cancer genetic testing. Main Outcomes and Measures: Frequency of and time to amended reports; frequency and types of variant reclassification. Results: From 2006 through 2018, 1.45 million individuals (median [interquartile range] age at testing, 49 years [40.69-58.31 years], 95.6% women) had genetic testing, and 56.6% (n = 821 724) had a personal history of cancer. A total of 1.67 million initial tests were reported and 59 955 amended reports were issued due to variant reclassification. Overall, 6.4% (2868 of 44 777) of unique variants were reclassified. Reclassification to a different clinical category was rare among unique variants initially classified as pathogenic or likely pathogenic (0.7%, 61 of 9112) or benign or likely benign (0.2%, 15 of 8995). However, 7.7% (2048 of 26 670) of unique variants of uncertain significance were reclassified: 91.2% (1867 of 2048) were downgraded to benign or likely benign (median time to amended report, 1.17 years), 8.7% (178 of 2048) were upgraded to pathogenic or likely pathogenic variants (median time to amended report, 1.86 years). Because most variants were observed in more than 1 individual, 24.9% (46 890 of 184 327) of all reported variants of uncertain significance were reclassified. Conclusions and Relevance: Following hereditary cancer genetic testing at a single commercial laboratory, 24.9% of variants of uncertain significance were reclassified, which included both downgrades and upgrades. Further research is needed to assess generalizability of the findings for other laboratories, as well as the clinical consequences of the reclassification as a component of a genetic testing program.

Clinical testing with a panel of 25 genes associated with increased cancer risk results in a significant increase in clinically significant findings across a broad range of cancer histories.

Genetic testing for inherited cancer risk is now widely used to target individuals for screening and prevention. However, there is limited evidence available to evaluate the clinical utility of various testing strategies, such as single-syndrome, single-cancer, or pan-cancer gene panels. Here we report on the outcomes of testing with a 25-gene pan-cancer panel in a consecutive series of 252,223 individuals between September 2013 and July 2016. The majority of individuals (92.8%) met testing criteria for Hereditary Breast and Ovarian Cancer (HBOC) and/or Lynch syndrome (LS). Overall, 17,340 PVs were identified in 17,000 (6.7%) of the tested individuals. The PV positive rate was 9.8% among individuals with a personal cancer history, compared to 4.7% in unaffected individuals. PVs were most common in BRCA1/2 (42.2%), other breast cancer (BR) genes (32.9%), and the LS genes (13.2%). Half the PVs identified among individuals who met only HBOC testing criteria were in genes other than BRCA1/2. Similarly, half of PVs identified in individuals who met only LS testing criteria were in non-LS genes. These findings suggest that genetic testing with a pan-cancer panel in this cohort provides improved clinical utility over traditional single-gene or single-syndrome testing.

Clinical Variant Classification: A Comparison of Public Databases and a Commercial Testing Laboratory.

BACKGROUND: There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, the well-documented limitations of these databases call into question how often clinicians will encounter discordant variant classifications that may introduce uncertainty into patient management. Here, we evaluate discordance in BRCA1 and BRCA2 variant classifications between a single commercial testing laboratory and a public database commonly consulted in clinical practice. MATERIALS AND METHODS: BRCA1 and BRCA2 variant classifications were obtained from ClinVar and compared with the classifications from a reference laboratory. Full concordance and discordance were determined for variants whose ClinVar entries were of the same pathogenicity (pathogenic, benign, or uncertain). Variants with conflicting ClinVar classifications were considered partially concordant if ≥1 of the listed classifications agreed with the reference laboratory classification. RESULTS: Four thousand two hundred and fifty unique BRCA1 and BRCA2 variants were available for analysis. Overall, 73.2% of classifications were fully concordant and 12.3% were partially concordant. The remaining 14.5% of variants had discordant classifications, most of which had a definitive classification (pathogenic or benign) from the reference laboratory compared with an uncertain classification in ClinVar (14.0%). CONCLUSION: Here, we show that discrepant classifications between a public database and single reference laboratory potentially account for 26.7% of variants in BRCA1 and BRCA2. The time and expertise required of clinicians to research these discordant classifications call into question the practicality of checking all test results against a database and suggest that discordant classifications should be interpreted with these limitations in mind. IMPLICATIONS FOR PRACTICE: With the increasing use of clinical genetic testing for hereditary cancer risk, accurate variant classification is vital to ensuring appropriate medical management. There is a growing move to consult public databases following receipt of a genetic test result from a clinical laboratory; however, we show that up to 26.7% of variants in BRCA1 and BRCA2 have discordant classifications between ClinVar and a reference laboratory. The findings presented in this paper serve as a note of caution regarding the utility of database consultation.

Detection of somatic variants in peripheral blood lymphocytes using a next generation sequencing multigene pan cancer panel.

Next Generation Sequencing (NGS) multigene panels, which are routinely used to assess hereditary cancer risk, can detect both inherited germline variants and somatic variants in cancer-risk genes. We evaluated the frequency and distribution of likely somatic Pathogenic and Likely Pathogenic variants (PVs) detected in >220,000 individuals who underwent clinical testing with a 25-gene panel between September 2013 and March 2016. Likely somatic PVs are defined as variants with NGS read frequencies from 10% to 30%. Overall, 137 (0.06%) individuals were identified as carrying likely somatic PVs, most commonly in TP53 (73), CHEK2 (27), and ATM (20). Among this group, a second PV with a NGS read frequency consistent with a germline variant within the same gene or a different gene on the panel was detected in 21 individuals (15.3%), which is similar to the detection rate in our general testing population. Likely somatic PVs accounted for 38.8% of all PVs in TP53. In comparison, likely somatic PVs accounted for <1% of PVs in most other genes. Likely somatic PVs were more frequently identified in older individuals (p < 0.001). Additional studies are ongoing to further investigate the incidence and clinical implications of somatic variants, enabling the appropriate medical management for these patients.

Prevalence of undiagnosed type 2 diabetes in patients admitted with acute coronary syndrome: the utility of easily reproducible screening methods.

BACKGROUND: Despite the recognition of the importance of diagnosing dysglycaemia in patients with acute coronary syndrome (ACS) there remains a lack of consensus on the best screening modality. Our primary aims were to determine the prevalence of undiagnosed dysglycaemia and to compare the OGTT and HbA1c criteria for diagnosis of T2DM in patients admitted to hospital with ACS at baseline and at 3-months. We also aimed to investigate the role of a screening algorithm and a predictor score to define glucose tolerance in this population. METHODS: A prospective study in which patients admitted with ACS to two UK teaching hospitals were assessed at baseline and 3 months follow-up. RESULTS: The prevalence of diabetes at baseline was 20% and 16% based on OGTT and HbA1c criteria respectively. Forty three (43) % of the patients with T2DM based on OGTT would have been missed by the HbA1c criteria at baseline. Our screening algorithm identified 87% of patients with T2DM diagnosed with OGTT. Diabetes Predictor score had better sensitivity (>80%) and negative predictive value (>90%) compared to HbA1c criteria. Two thirds of participants with IGS and a third with T2DM changed their glycaemic status at 3 months. CONCLUSIONS: Only 48% of the patients admitted with ACS had normo-glycaemia based on OGTT. OGTT and HbA1c identified two different populations of patients with dysglycaemia with the HbA1c criteria missing almost half the patients with T2DM based on OGTT. Compared to HbA1c criteria our diabetes algorithm and diabetes predictor score had a better correlation with OGTT criteria.

Optimization of quality assurance to increase clinical utility and cost effectiveness of hereditary cancer testing.

AIM: To evaluate one laboratory's hereditary cancer testing clinical quality assurance (QA) process to minimize test-ordering errors. METHODS: The proportion of tests canceled/revised due to pre-analytic QA processes or provider consultation prior to test ordering were determined and the resulting health cost savings were estimated. RESULTS: Over 2000 genetic test orders were canceled/revised over a 1-year period due to the laboratory QA process, saving US$5,801,832 in healthcare costs. Consultation with healthcare providers prior to submitting genetic test requests resulted in 37 canceled/revised test orders in a 2-week period, which extrapolates to a savings of US$3,049,098 over 1 year. CONCLUSION: QA processes can contribute to the curtailment of healthcare costs through canceling or revising test orders.

Increased Identification of Candidates for High-Risk Breast Cancer Screening Through Expanded Genetic Testing.

PURPOSE: Breast MRI screening is recommended for women with a >20% lifetime risk for breast cancer on the basis of estimates derived from risk models dependent largely on family history. Alternatively, a >20% lifetime risk can be established through genetic testing of BRCA1 and BRCA2, as well as a growing selection of other genes associated with inherited breast cancer risk. The aim of this study was to quantify the impact of testing for genes other than BRCA1/2 and the extent to which mutation carriers in these genes would have been identified as candidates for enhanced screening on the basis of family history alone. METHODS: Women were tested with a 25-gene hereditary cancer panel including BRCA1/2 and 7 additional genes known to be associated with a >20% lifetime risk for breast cancer (ATM, CHEK2, PALB2, TP53, PTEN, CDH1, and STK11). Women found to carry pathogenic variants (PVs) were evaluated with the Claus model to assess whether they would have been found to be at >20% lifetime risk on the basis of family history. RESULTS: In total, 9,751 PVs in the selected breast cancer risk genes were identified in 9,641 women. BRCA1/2 accounted for 59.1% of the PVs, and 38.8% were in ATM, CHEK2, or PALB2. Only 24.7% of all women with PVs found in any gene reached the >20% lifetime risk threshold using the Claus model. CONCLUSIONS: Expanding genetic testing beyond BRCA1/2 significantly increases the number of women who are candidates for breast MRI and other risk reduction measures, most of whom would not have been identified through family history assessment.

Can HbA1c detect undiagnosed diabetes in acute medical hospital admissions?

OBJECTIVE: To study hyperglycaemia in acute medical admissions to Irish regional hospital. RESEARCH DESIGN AND METHODS: From 2005 to 2007, 2061 white Caucasians, aged >18 years, were admitted by 1/7 physicians. Those with diabetes symptoms/complications but no previous record of hyperglycaemia (n=390), underwent OGTT with concurrent HbA1c in representative subgroup (n=148). Comparable data were obtained for 108 primary care patients at risk of diabetes. RESULTS: Diabetes was diagnosed immediately by routine practice in 1% (22/2061) [aged 36 (26-61) years (median IQ range)/55% (12/22) male] with pre-existing diabetes/dysglycaemia present in 19% (390/2061) [69 (58-80) years/60% (235/390) male]. Possible diabetes symptoms/complications were identified in 19% [70 (59-79) years/57% (223/390) male] with their HbA1c similar to primary care patients [54 (46-61) years], 5.7 (5.3-6.0)%/39 (34-42)mmol/mol (n=148) vs 5.7 (5.4-6.1)%/39 (36-43)mmol/mol, p=0.35, but lower than those diagnosed on admission, 10.2 (7.4-13.3)%/88 (57-122)mmol/mol, p<0.001. Their fasting plasma glucose (FPG) was similar to primary care patients, 5.2 (4.8-5.7) vs 5.2 (4.8-5.9) mmol/L, p=0.65, but 2hPG higher, 9.0 (7.3-11.4) vs 5.5 (4.4-7.5), p<0.001. HbA1c identified diabetes in 10% (15/148) with 14 confirmed on OGTT but overall 32% (48/148) were in diabetic range on OGTT. The specificity of HbA1c in 2061 admissions was similar to primary care, 99% vs 96%, p=0.20, but sensitivity lower, 38% vs 93%, p<0.001 (63% on FPG/23% on 2hPG, p=0.037, in those with possible symptoms/complications). CONCLUSION: HbA1c can play a diagnostic role in acute medicine as it diagnosed another 2% of admissions with diabetes but the discrepancy in sensitivity shows that it does not reflect transient/acute hyperglycaemia resulting from the acute medical event.

The effect of glibenclamide on insulin secretion at normal glucose concentrations.

AIMS/HYPOTHESIS: The aim of this study was to investigate the incremental and proportional effect of a sulfonylurea on insulin secretion rates at low, elevated and high blood glucose, using parallel groups with ascending or descending glucose steps to minimise potential biases of a single stepped clamp order. METHODS: Following 14 days on placebo or glibenclamide (2.5 mg) tablets twice daily, separated by 14 days washout, 19 type 2 diabetic patients had ascending or descending three-step hyperinsulinaemic glucose clamps at 4, 8 and 12 mmol/l. C-peptide secretion was estimated by two-compartment C-peptide deconvolution. RESULTS: Patients in the ascending glucose steps group (n = 10) had mean (SD) age of 60.3 (6.5) years, BMI of 29.8 (4.9) kg/m(2) and fasting glucose on diet alone of 10.6 (2.9) mmol/l; while those in the descending glucose steps group (n = 9) had mean age of 58.2 (8.0) years, BMI of 30.5 (5.4) kg/m(2) and fasting glucose on diet alone of 9.8 (2.2) mmol/l. The geometric means (95% CI) of C-peptide secretion rates on placebo for glucose at 4.0, 8.0 and 12.0 mmol/l were 63 (46, 86), 143 (105, 195) and 205 (149, 281) pmol/min, respectively. On glibenclamide, this increased by 140 (99, 181), 126 (85, 167) and 158 (117, 199) pmol/min, respectively (p < 0.001 vs placebo). The absolute increment was significant (p < 0.001) and independent of clamp glucose concentration (p = 0.54). The proportional increase was greater at 4 mmol/l: 2.8-fold (2.4, 3.2), compared with 1.8-fold (1.5, 2.0) and 1.7-fold (1.4, 1.9) at 8 and 12 mmol/l, respectively (p < 0.001). CONCLUSIONS/INTERPRETATION: At low-normal glucose, glibenclamide exerted a disproportionate effect on insulin secretion. This study highlights the risks of hypoglycaemia when aiming for tight glucose control on this agent.

Comparison of IFCC-calibrated HbA(1c) from laboratory and point of care testing systems.

OBJECTIVE: WHO, IDF and ADA recommend HbA(1c) ≥6.5% (48 mmol/mol) for diagnosis of diabetes with pre-diabetes 6.0% (42 mmol/mol) [WHO] or 5.7% (39 mmol/mol) [ADA] to 6.4% (47 mmol/mol). We have compared HbA(1c) from several methods for research relating glycaemic markers. RESEARCH DESIGN AND METHODS: HbA1c was measured in EDTA blood from 128 patients with diabetes on IE HPLC analysers (Bio-Rad Variant II NU, Menarini HA8160 and Tosoh G8), point of care systems, POCT, (A1cNow+ disposable cartridges and DCA 2000(®)+ analyser), affinity chromatography (Primus Ultra2) and the IFCC secondary reference method (Menarini HA8160 calibrated using IFCC SRM protocol). RESULTS: Median (IQ range) on IFCC SRM was 7.5% (6.8-8.4) (58(51-68) mmol/mol) HbA(1c) with minimum 5.3%(34 mmol/mol)/maximum 11.9%(107 mmol/mol). There were positive offsets between IFCC SRM and Bio-Rad Variant II NU, mean difference (1SD), +0.33%(0.17) (+3.6(1.9) mmol/mol), r(2)=0.984, p<0.001 and Tosoh G8, +0.22%(0.20) (2.4(2.2) mmol/mol), r(2)=0.976, p<0.001 with a very small negative difference -0.04%(0.11) (-0.4(1.2) mmol/mol), r(2)=0.992, p<0.001 for Menarini HA8160. POCT methods were less precise with negative offsets for DCA 2000(®)+ analyser -0.13%(0.28) (-1.4(3.1) mmol/mol), r(2)=0.955, p<0.001 and A1cNow+ cartridges -0.70%(0.67) (-7.7(7.3) mmol/mol), r(2)=0.699, p<0.001 (n=113). Positive biases for Tosoh and Bio-Rad (compared with IFCC SRM) have been eliminated by subsequent revision of calibration. CONCLUSIONS: Small differences observed between IFCC-calibrated and NGSP certified methods across a wide HbA(1c) range were confirmed by quality control and external quality assurance. As these offsets affect estimates of diabetes prevalence, the analyser (and calibrator) employed should be considered when evaluating diagnostic data.

Preanalytical, analytical, and computational factors affect homeostasis model assessment estimates.

OBJECTIVE: We investigated how beta-cell function and insulin sensitivity or resistance are affected by the type of blood sample collected or choice of insulin assay and homeostatis model assessment (HOMA) calculator (http://www.dtu.ox.ac.uk). RESEARCH DESIGN AND METHODS: Insulin was measured using 11 different assays in serum and 1 assay in heparinized plasma. Fasting subjects with normoglycemia (n = 12), pre-diabetes, i.e., impaired fasting glucose or impaired glucose tolerance (n = 18), or type 2 diabetes (n = 67) were recruited. Patients treated with insulin or those who were insulin antibody-positive were excluded. HOMA estimates were calculated using specific insulin (SI) or radioimmunoassay (RIA) calculators (version 2.2). RESULTS: All glucose values were within model (HOMA) limits but not all insulin results, as 4.3% were <20 pmol/l and 1% were >300 pmol/l. beta-Cell function derived from different insulin assays ranged from 67 to 122% (median) for those with normoglycemia (P = 0.026), from 89 to 138% for those with pre-diabetes (P = 0.990), and from 50 to 81% for those with type 2 diabetes (P < 0.0001). Furthermore, insulin resistance ranged from 0.8 to 2.0 (P = 0.0007), from 1.9 to 3.2 (P = 0.842), and from 1.5 to 2.9 (P < 0.0001), respectively. This twofold variation in HOMA estimates from the various insulin assays studied in serum may be significant metabolically. Insulin was 15% lower in heparinized plasma (used in the original HOMA study) compared with serum, which is now more commonly used. beta-Cell function differed by 11% and insulin resistance by 15% when estimates derived from specific insulin were calculated using the RIA rather than the SI calculator. CONCLUSIONS: To enable comparison of HOMA estimates among individuals and different research studies, preanalytical factors and calculator selection should be standardized with insulin assays traceable to an insulin reference method procedure.