The Utility of Prostate-Specific Membrane Antigen-11 PET in Detection and Management of Central Nervous System Neoplasms.

ABSTRACT: We present a case series of 5 patients diagnosed with schwannoma and 1 patient diagnosed with astrocytoma who underwent PSMA PET imaging for tumor detection. We retrospectively analyzed the records of 4 male and 2 female patients (mean age, 53.2 ± 13.2) who underwent PSMA PET imaging between March and September 2023. PET interpretation showed increased Ga-PSMA-11 accumulation in all patients with a mean SUV max of 3.11 ± 1.8. This series underscores PSMA PET's potential for CNS neoplasm detection.

Trends in utilization of contralateral prophylactic mastectomy among different age, racial and ethnic groups.

Background: The use of contralateral prophylactic mastectomy (CPM) has increased over the last two decades with variations in the frequency of reconstruction. The objective of this cohort study is to elucidate the use of CPM and reconstruction among underrepresented racial and ethnic groups and women over 65 years. Methods: Women over 18 years, diagnosed with stages I to III breast cancer who underwent mastectomy from 2004-2017 were identified in the National Cancer Database (NCDB) and grouped into CPM vs. non-CPM. Multivariable analyses were used to examine the associations between CPM and reconstruction with sociodemographic and clinical factors. Results: A total of 571,649 patients were identified. Patients who underwent CPM were under 50 years (45.9%), White (88.4%) and with private insurance (73.5%). On multivariable analysis, women over 65 years [odds ratio (OR): 0.18, P<0.001], non-White (Black, OR: 0.56, P<0.001) and without private insurance (uninsured, OR: 0.50, P<0.001) had decreased odds of CPM. Women over 65 years (OR: 0.11, P<0.001), non-White (Asian/Pacific Islander, OR: 0.58, P<0.001) and without private insurance (Medicaid, OR: 0.41, P<0.001) had decreased odds of reconstruction. Conclusions: Non-White women and women over the age of 65 years were less likely to have CPM or reconstruction than their White counterparts from 2004 to 2017. Research is needed to understand factors impacting decision-making.

A Review of Diabetes Prediction Equations in African Descent Populations.

Background: Predicting undiagnosed diabetes is a critical step toward addressing the diabetes epidemic in populations of African descent worldwide. Objective: To review characteristics of equations developed, tested, or modified to predict diabetes in African descent populations. Methods: Using PubMed, Scopus, and Embase databases, a scoping review yielded 585 research articles. After removal of duplicates (n = 205), 380 articles were reviewed. After title and abstract review 328 articles did not meet inclusion criteria and were excluded. Fifty-two articles were retained. However, full text review revealed that 44 of the 52 articles did not report findings by AROC or C-statistic in African descent populations. Therefore, eight articles remained. Results: The 8 articles reported on a total of 15 prediction equation studies. The prediction equations were of two types. Prevalence prediction equations (n = 9) detected undiagnosed diabetes and were based on non-invasive variables only. Non-invasive variables included demographics, blood pressure and measures of body size. Incidence prediction equations (n = 6) predicted risk of developing diabetes and used either non-invasive variables or both non-invasive and invasive. Invasive variables required blood tests and included fasting glucose, high density lipoprotein-cholesterol (HDL), triglycerides (TG), and A1C. Prevalence prediction studies were conducted in the United States, Africa and Europe. Incidence prediction studies were conducted only in the United States. In all these studies, the performance of diabetes prediction equations was assessed by area under the receiver operator characteristics curve (AROC) or the C-statistic. Therefore, we evaluated the efficacy of these equations based on standard criteria, specifically discrimination by either AROC or C-statistic were defined as: Poor (0.50 - 0.69); Acceptable (0.70 - 0.79); Excellent (0.80 - 0.89); or Outstanding (0.90 - 1.00). Prediction equations based only on non-invasive variables reported to have poor to acceptable detection of diabetes with AROC or C-statistic 0.64 - 0.79. In contrast, prediction equations which were based on both non-invasive and invasive variables had excellent diabetes detection with AROC or C-statistic 0.80 - 0.82. Conclusion: Equations which use a combination of non-invasive and invasive variables appear to be superior in the prediction of diabetes in African descent populations than equations that rely on non-invasive variables alone.

A1C Underperforms as a Diagnostic Test in Africans Even in the Absence of Nutritional Deficiencies, Anemia and Hemoglobinopathies: Insight From the Africans in America Study.

Introduction: To improve detection of undiagnosed diabetes in Africa, there is movement to replace the OGTT with A1C. The performance of A1C in the absence of hemoglobin-related micronutrient deficiencies, anemia and heterozygous hemoglobinopathies is unknown. Therefore, we determined in 441 African-born blacks living in America [male: 65% (281/441), age: 38 ± 10 y (mean ± SD), BMI: 27.5 ± 4.4 kg/m2] (1) nutritional and hematologic profiles and (2) glucose tolerance categorization by OGTT and A1C. Methods: Hematologic and nutritional status were assessed. Hemoglobin <11 g/dL occurred in 3% (11/441) of patients and led to exclusion. A1C and OGTT were performed in the remaining 430 participants. ADA thresholds for A1C and OGTT were used. Diagnosis by A1C required meeting either A1C-alone or A1C&OGTT criteria. Diagnosis by OGTT-alone required detection by OGTT and not A1C. Results: Hemoglobin, mean corpuscular volume and red blood cell distribution width were 14.0 ± 1.3 g/dL, 85.5 ± 5.3 fL, and 13.2 ± 1.2% respectively. B12, folate, and iron deficiency occurred in 1% (5/430), 0% (0/430), and 4% (12/310), respectively. Heterozygous hemoglobinopathy prevalence was 18% (78/430). Overall, diabetes prevalence was 7% (32/430). A1C detected diabetes in 32% (10/32) but OGTT-alone detected 68% (22/32). Overall prediabetes prevalence was 41% (178/430). A1C detected 57% (102/178) but OGTT-alone identified 43% (76/178). After excluding individuals with heterozygous hemoglobinopathies, the rate of missed diagnosis by A1C of abnormal glucose tolerance did not change (OR: 0.99, 95% CI: 0.61, 1.62). Conclusions: In nutritionally replete Africans without anemia or heterozygous hemoglobinopathy, if only A1C is used, ~60% with diabetes and ~40% with prediabetes would be undiagnosed. Clinical Trial Registration:: www.ClinicalTrials.gov, Identifier: NCT00001853.