Racial/ethnic differences in average CA125 and CA15.3 values and its correlates among postmenopausal women in the USA

Variables Affecting CA15.3 Tumor Antigen Expression and Antibodies against It in Female National Health and Nutritional Survey Participants

BACKGROUND

Cancers of ductal origin often express glycoprotein mucin 1 (MUC1), also known as CA15.3, with higher levels leading to poor prognosis. Conversely, anti-MUC1 antibodies develop in some patients, leading to better prognosis. We sought to identify epidemiologic factors associated with CA15.3 antigen or antibody levels.

METHODS

Levels of CA15.3 antigen and anti-CA15.3 IgG antibodies were measured in archived sera from 2,302 mostly healthy women from the National Health and Nutritional Survey; and epidemiologic predictors of their levels were examined using multivariate and correlational analyses.

RESULTS

Among racial groups, Black women had the highest levels of CA15.3 antigen and lowest levels of antibodies. Increasing body mass index and current smoking were associated with low anti-CA15.3 antibody levels. Low CA15.3 antigen levels were seen in oral contraceptive users and high levels in women who were pregnant or lactating at the time of blood collection, with the latter group also having high antibody levels. Past reproductive events associated with high antigen levels included the following: later age at menarche, having given birth, and history of endometriosis. Lower antigen levels were seen with increasing duration of OC use. Anti-CA15.3 antibody levels decreased with an increasing estimated number of ovulatory years.

CONCLUSIONS

Key determinants of CA.15.3 antigen or antibody levels include the following: race, body mass index, smoking, later menarche, childbirth, number of ovulatory cycles, and endometriosis.

IMPACT

This study supports the premise that known epidemiologic factors affecting risk for or survival after MUC1-expressing cancers may, at least partially, operate through their association with CA15.3 antigen or antibody levels.

Differences in Serum miRNA Profiles by Race, Ethnicity, and Socioeconomic Status: Implications for Developing an Equitable Ovarian Cancer Screening Test

Serum miRNAs are promising biomarkers for several clinical conditions, including ovarian cancer. To inform equitable implementation of these tests, we investigated the effects of race, ethnicity, and socioeconomic status on serum miRNA profiles. Serum samples from a large institutional biobank were analyzed using a custom panel of 179 miRNA species highly expressed in human serum, measured using the Abcam Fireplex assay via flow cytometry. Data were log-transformed prior to analysis. Differences in miRNA by race and ethnicity were assessed using logistic regression. Pairwise t tests analyzed racial and ethnic differences among eight miRNAs previously associated with ovarian cancer risk. Pearson correlations determined the relationship between mean miRNA expression and the social deprivation index (SDI) for Massachusetts residents. Of 1,586 patients (76.9% white, non-Hispanic), compared with white, non-Hispanic patients, those from other racial and ethnic groups were younger (41.9 years ± 13.2 vs. 51.3 ± 15.1, P < 0.01) and had fewer comorbidities (3.5 comorbidities ± 2.7 vs. 4.6 ± 2.8, P < 0.01). On logistic regression, miRNAs predicted race and ethnicity at an AUC of 0.69 (95% confidence interval, 0.66-0.72), which remained consistent when stratified by most comorbidities. Among eight miRNAs previously associated with ovarian cancer risk, seven significantly varied by race and ethnicity (all P < 0.01). There were no significant differences in SDI for any of these eight miRNAs. miRNA expression is significantly influenced by race and ethnicity, which remained consistent after controlling for confounders. Understanding baseline differences in biomarker test characteristics prior to clinical implementation is essential to ensure instruments perform comparably across diverse populations.

PREVENTION RELEVANCE

This study aimed to understand factors affecting miRNA expression, to ensure we create equitable screening tests for ovarian cancer that perform well in diverse populations. The goal is to ensure that we are detecting ovarian cancer cases earlier (secondary prevention) in women of all races, ethnic backgrounds, and socioeconomic means.

Early Ovarian Cancer Detection in the Age of Fallopian Tube Precursors: A Systematic Review

OBJECTIVE

To determine biomarkers other than CA 125 that could be used in identifying early-stage ovarian cancer.

DATA SOURCES

Ovid MEDLINE ALL, EMBASE, Web of Science Core Collection, ScienceDirect, Clinicaltrials.gov , and CAB Direct were searched for English-language studies between January 2008 and April 2023 for the concepts of high-grade serous ovarian cancer, testing, and prevention or early diagnosis.

METHODS OF STUDY SELECTION

The 5,523 related articles were uploaded to Covidence. Screening by two independent reviewers of the article abstracts led to the identification of 245 peer-reviewed primary research articles for full-text review. Full-text review by those reviewers led to the identification of 131 peer-reviewed primary research articles used for this review.

TABULATION, INTEGRATION, AND RESULTS

Of 131 studies, only 55 reported sensitivity, specificity, or area under the curve (AUC), with 36 of the studies reporting at least one biomarker with a specificity of 80% or greater specificity or 0.9 or greater AUC.

CONCLUSION

These findings suggest that although many types of biomarkers are being tested in ovarian cancer, most have similar or worse detection rates compared with CA 125 and have the same limitations of poor detection rates in early-stage disease. However, 27.5% of articles (36/131) reported biomarkers with better sensitivity and an AUC greater than 0.9 compared with CA 125 alone and deserve further exploration.

Unsupervised machine learning method for indirect estimation of reference intervals for chronic kidney disease in the Puerto Rican population

Reference intervals (RIs) for clinical laboratory values are extremely important for diagnostics and treatment of patients. However, the determination of these ranges is costly and time-consuming. As a result, often different unverified RIs are used in practice for the same analyte and the same range is used for all patients despite evidence that the values are gender, age, and ethnicity dependent. Moreover, the abnormal flags are rudimentary, merely indicating if a value is within the RI. At the same time, clinical lab data generated in the everyday medical practice contains a wealth of information, that given the correct methodology, can help determine the RIs for each specific segment of the population, including populations that suffer from health disparities. In this work, we develop unsupervised machine learning methods, based on Gaussian mixtures, to determine RIs of analytes related to chronic kidney disease, using millions of routine lab results for the Puerto Rican population. We show that the measures are both gender and age dependent and we find evidence for normal age-related organ function deterioration and failure. We also show that the joint distribution of measures improves the diagnostic value of the lab results.

Cancer Screening Experiences of Black Breast and Ovarian Cancer Patients and Family Members

Black women experience disproportionate rates of advanced breast cancer diagnoses and mortality. Mammography is a proven and effective tool in early breast cancer detection and impacts patient outcomes. We interviewed Black women with a personal or family history of breast and/or ovarian cancer to understand their screening experiences and views. N = 61 individuals completed an interview. Interview transcripts were qualitatively analyzed for themes regarding clinical experiences, guideline adherence, and family sharing specific to Black women and their families. Most participants were college educated with active health insurance. Women in this cohort were knowledgeable about the benefits of mammography and described few barriers to adhering to annual mammogram guidelines. Some with first-degree family history were frustrated at insurance barriers to mammography before the age of 40. Participants were generally comfortable encouraging family and friends to receive mammograms and expressed a desire for a similar screening tool for ovarian cancer. However, they expressed concern that factors such as screening awareness and education, lack of insurance coverage, and other systematic barriers might prevent other Black women from receiving regular screening. Black women in this cohort reported high adherence to mammography guidelines, but expressed concern about cultural and financial barriers that may impact cancer screening access in the population more generally and contribute to disparities. Participants noted the importance of frank and open discussions of breast cancer screening in their families and community as a means of improving awareness.

Current status and challenges in establishing reference intervals based on real-world data

Reference intervals (RIs) are the cornerstone for evaluation of test results in clinical practice and are invaluable in judging patient health and making clinical decisions. Establishing RIs based on clinical laboratory data is a branch of real-world data mining research. Compared to the traditional direct method, this indirect approach is highly practical, widely applicable, and low-cost. Improving the accuracy of RIs requires not only the collection of sufficient data and the use of correct statistical methods, but also proper stratification of heterogeneous subpopulations. This includes the establishment of age-specific RIs and taking into account other characteristics of reference individuals. Although there are many studies on establishing RIs by indirect methods, it is still very difficult for laboratories to select appropriate statistical methods due to the lack of formal guidelines. This review describes the application of real-world data and an approach for establishing indirect reference intervals (iRIs). We summarize the processes for establishing iRIs using real-world data and analyze the principle and applicable scope of the indirect method model in detail. Moreover, we compare different methods for constructing growth curves to establish age-specific RIs, in hopes of providing laboratories with a reference for establishing specific iRIs and giving new insight into clinical laboratory RI research. (201 words).