Sokoll, Lori J.

Importance Although the Martin-Hopkins equation is widely validated and used to estimate low-density lipoprotein cholesterol (LDL-C) for clinical care, a simplified equation could streamline implementation and enable broader adoption. Objective To develop a simplified machine learning–based alternative to the Martin-Hopkins equation using multivariate adaptive regression splines (LDL-C–MH-MARS) and compare its performance with the Friedewald (LDL-C–F), Sampson–National Institutes of Health (LDL-C–S), Modified Sampson (LDL-C–MS), and Martin-Hopkins (LDL-C–MH) equations. Design, Setting, and Participants The Very Large Database of Lipids is a cross-sectional database of clinical lipid measurements from a population-representative convenience sample of adult and pediatric patients. Lipid measurements were performed by Vertical Auto Profile ultracentrifugation between October 1, 2015, and June 30, 2019. The study included patients with complete lipid panel data who were randomly assigned to a training set and a test set. External validation against preparative ultracentrifugation-based LDL-C measurements was performed in reference laboratory datasets from the Mayo Clinic (broad LDL-C concentrations) and the Further Cardiovascular Outcomes Research With Proprotein Convertase Subtilisin/Kexin Type 9 (PCSK9) Inhibition in Subjects with Elevated Risk (FOURIER) trial (observations from patients with low LDL-C concentrations while taking evolocumab). Study data were analyzed from January to October 2025. Exposures LDL-C–F, LDL-C–S, LDL-C–MS, LDL-C–MH, and LDL-C–MH-MARS equations. Main Outcomes and Measures Accuracy of estimated vs ultracentrifugation-measured LDL-C concentration based on bias, root mean square error (RMSE), and concordance by guideline-based categories. Results The study included 4 939 528 patients (mean [SD] age, 56 [16] years; 2 635 486 female [53%]) with complete lipid panel data who were randomly assigned to a training set (n = 3 292 889) and a test set (n = 1 646 639). LDL-C–MH-MARS equation demonstrated a very low median (IQR) bias of −0.1 (−2.1 to 1.8) mg/dL (to convert to millimoles per liter, multiply by 0.0259), comparable with LDL-C–MH. The median (IQR) difference between the MARS and original Martin-Hopkins equations (ie, LDL-C–MH-MARS – LDL-C–MH) was −0.5 (−1.2 to 0) mg/dL, further suggesting comparability between the 2 methods. The RMSE was smallest for LDL-C–MH-MARS (4.7 mg/dL) and LDL-C–MH (4.9 mg/dL), followed by LDL-C–S (5.8 mg/dL), LDL-C-MS (6.0 mg/dL), and LDL-C–F (7.2 mg/dL). The proportion of patients correctly classified according to clinical categories was nearly identical for LDL-C–MH-MARS (89.7%) and LDL-C–MH (89.6%) but lower for LDL-C–S (86.3%), LDL-C–MS (84.7%), and LDL-C–F (83.1%). The LDL-C–MH-MARS, LDL-C–MH, LDL-C–MS, LDL-C–S, and LDL-C–F equations underestimated LDL-C concentration in 16%, 17%, 28%, 39%, and 60%, respectively, when classifying LDL-C less than 70 mg/dL in patients with triglyceride concentrations of 200 to 399 mg/dL (to convert to millimoles per liter, multiply by 0.0113). The patterns of results were similar in external validation datasets, with the LDL-C–MH-MARS and LDL-C–MH equations demonstrating the highest accuracy. Conclusions and Relevance Study results suggest that the new machine learning–based LDL-C equation provided results comparable with those of the original Martin-Hopkins method while simplifying implementation to a single equation.

Abstract Purpose: We previously demonstrated that high levels of circulating methylated DNA are associated with subsequent disease progression in women with metastatic breast cancer (MBC). In this study, we evaluated the clinical utility of a novel liquid biopsy-breast cancer methylation (LBx-BCM) prototype assay using the GeneXpert cartridge system for early assessment of disease progression in MBC. Experimental Design: The 9-marker LBx-BCM prototype assay was evaluated in TBCRC 005, a prospective biomarker study, using plasma collected at baseline, week 4, and week 8 from 144 patients with MBC. Results: At week 4, patients with MBC with high cumulative methylation (CM) had a significantly shorter median PFS (2.88 months vs. 6.60 months, P = 0.001) and OS (14.52 months vs. 22.44 months, P = 0.005) compared with those with low CM. In a multivariable model, high versus low CM was also associated with shorter PFS (HR, 1.90; 95% CI, 1.20–3.01; P = 0.006). Change in CM from baseline to week 4 (OR, 4.60; 95% CI, 1.77–11.93; P = 0.002) and high levels of CM at week 4 (OR, 2.78; 95% CI, 1.29–5.99; P = 0.009) were associated with progressive disease at the time of first restaging. A robust risk model based on week 4 circulating CM levels was developed to predict disease progression as early as 3 months after initiating a new treatment. Conclusions: The automated LBx-BCM prototype assay is a promising clinical tool for detecting disease progression a month after initiating treatment in women with MBC undergoing routine care. The next step is to validate its clinical utility for specific treatments.

Abstract Context. —In proficiency testing surveys, there are differences in the values reported by users of various analytic methods. Two contributors to this variation are calibrator bias and matrix effects of proficiency testing materials. Objectives. —(1) To quantify the biases of the analytic methods used to measure thyroid-stimulating hormone, thyroxine, triiodothyronine, free thyroxine, and free triiodothyronine levels; (2) to determine if these biases are within allowable limits; and (3) to ascertain if proficiency testing materials correctly identify these biases. Design. —A fresh frozen serum specimen was mailed as part of the 2003 College of American Pathologists Ligand and Chemistry surveys. The means and SDs for each analytic method were determined for this sample as well as for a proficiency testing sample from both surveys. In the fresh frozen serum sample, target values for thyroxine and triiodothyronine were determined by isotope dilution/liquid chromatography/tandem mass spectrometry. All other target values in the study were the median of the means obtained for the various analytic methods. Main Outcome Measures. —Calibration biases were calculated by comparing the mean of each analytic method with the appropriate target values. These biases were evaluated against limits based on intra- and interindividual biological variation. Matrix effects of proficiency testing materials were assessed by comparing the rank of highest to lowest analytic method means (Spearman rank test) for each analyte. Participants. —Approximately 3900 clinical laboratories were enrolled in the College of American Pathologists Chemistry and Ligand surveys. Results. —The number of methods in the Ligand Survey that failed to meet the goals for bias was 7 of 17 for thyroid-stimulating hormone and 11 of 13 for free thyroxine. The failure rates were 12 of 16 methods for thyroxine, 8 of 11 for triiodothyronine, and 9 of 11 for free triiodothyronine. The means of the analytic method for the proficiency testing material correlated significantly ( P < .05) only with the fresh frozen serum means for thyroxine and thyroid-stimulating hormone in the Chemistry Survey and free triiodothyronine in the Ligand Survey. Conclusions. —A majority of the methods used in thyroid function testing have biases that limit their clinical utility. Traditional proficiency testing materials do not adequately reflect these biases.

Abstract Context. —Large disparities in prostate-specific antigen (PSA) results from different assays have been observed in the College of American Pathologists (CAP) Ligand Assay Survey, with interassay results varying severalfold. Survey specimens are predominately composed of free PSA and do not reflect the composition of typical patient specimens. Objectives. —To characterize a pilot material developed for CAP in which pooled sera samples were spiked with purified PSA and α 1 -antichymotrypsin–bound PSA at targeted concentrations and to compare it to CAP survey and reference materials. Design. —CAP survey, reference, and pilot materials were analyzed using 10 total PSA and 7 free PSA assays. These assays included Food and Drug Administration–approved assays and assays for research use only. Results. —Variability among the 10 total PSA methods was greatest for the 1997 ligand survey material (CV range, 56%–65%) followed by the pilot material (CV range, 10%–29%) and the reference material (CV range, 6%–13%). In contrast, interassay variability for the 7 free PSA methods was similar for the 3 preparations, with the exception of one specimen close to the limit of detection of the assays. As determined with the Hybritech Tandem-R method, the ligand survey specimens were essentially composed of all free PSA, whereas the reference and pilot materials were composed of approximately 10% and 35% free PSA, respectively. Conclusions. —The newly formulated pilot material prepared using a human base that contained defined concentrations of free PSA and α 1 -antichymotrypsin–bound PSA more closely resembled patient specimens and minimized differences among methods compared with the semen-supplemented original survey material.

Objective To examine the use of the Prostate Health Index ( PHI ) as a continuous variable in multivariable risk assessment for aggressive prostate cancer in a large multicentre US study. Materials and Methods The study population included 728 men, with prostate‐specific antigen ( PSA ) levels of 2–10 ng/ mL and a negative digital rectal examination, enrolled in a prospective, multi‐site early detection trial. The primary endpoint was aggressive prostate cancer, defined as biopsy Gleason score ≥7. First, we evaluated whether the addition of PHI improves the performance of currently available risk calculators (the Prostate Cancer Prevention Trial [ PCPT ] and European Randomised Study of Screening for Prostate Cancer [ ERSPC ] risk calculators). We also designed and internally validated a new PHI ‐based multivariable predictive model, and created a nomogram. Results Of 728 men undergoing biopsy, 118 (16.2%) had aggressive prostate cancer. The PHI predicted the risk of aggressive prostate cancer across the spectrum of values. Adding PHI significantly improved the predictive accuracy of the PCPT and ERSPC risk calculators for aggressive disease. A new model was created using age, previous biopsy, prostate volume, PSA and PHI , with an area under the curve of 0.746. The bootstrap‐corrected model showed good calibration with observed risk for aggressive prostate cancer and had net benefit on decision‐curve analysis. Conclusion Using PHI as part of multivariable risk assessment leads to a significant improvement in the detection of aggressive prostate cancer, potentially reducing harms from unnecessary prostate biopsy and overdiagnosis.

AbstractObjectivesWith clinical use of high‐sensitivity troponin I (hsTnI), more frequent troponin elevations will occur. However, the burden and implications of these elevations are not well understood. The authors quantified the prevalence of elevated hsTnI in patients presenting with possible acute coronary syndrome (ACS) who do not have elevated troponin with a current generation assay (cardiac troponin I [cTnI]) and determined the association of these newly detected elevations with a composite of all‐cause mortality and subsequent cardiac hospitalization.MethodsThis was a prospective observational study of 808 subjects evaluated for possible ACS and followed for up to 1 year. Troponin values were measured with hsTnI (Abbott Laboratories) and cTnI (Abbott and Beckman Coulter). Cardiac hospitalization was defined as hospitalization for ACS, revascularization, acute heart failure (AHF), or tachy/brady arrhythmia that occurred after the index emergency department (ED) visit or hospital discharge.ResultsForty subjects (5%) were diagnosed with ACS (26 myocardial infarction and 14 unstable angina). On the initial sample, the prevalence of elevated hsTnI among subjects with nonelevated cTnI was 9.2% using a gender‐neutral cutoff (95% confidence interval [CI] = 7.1% to 11.4%) and 11.1% using a gender‐specific cutoff (95% CI = 8.8% to 13.4%). Adjudicated diagnoses for subjects whose initial samples had elevated hsTnI but nonelevated cTnI (gender‐neutral cutoff) were as follows: three (4.6%) ACS, 15 (23.1%) AHF, three (4.6%) volume overload etiology unclear/noncardiac, three (4.6%) cardiac (non‐ACS), and 41 (63.1%) other. Of the 65 patients whose initial samples had hsTnI but nonelevated cTnI, eight developed cTnI elevation on subsequent serial sampling. After traditional cardiovascular risk factors and renal function were adjusted for, subjects with elevated initial hsTnI but nonelevated cTnI (initial and serial sampling) had a higher risk of all‐cause mortality and subsequent cardiac hospitalization than subjects with both nonelevated hsTnI and nonelevated cTnI (hazard ratio [HR] = 1.91, 95% CI = 1.14 to 3.19).ConclusionsOn the initial sample, 9% to 11% of subjects without cTnI elevation had hsTnI elevation. Although the majority of the patients with these newly detected hsTnI elevations did not have ACS, they had a higher risk for all‐cause mortality and subsequent cardiac hospitalization.