Reference interval limits for cancer biomarkers in geriatrics are rare because priority is given to the development of reference interval limits for those in the age range of 18–60 years, which are normally used for clinical trials study. The aim of this study was therefore to develop gender and age-specific reference interval limits for cancer markers CA19-9, CEA, CA 15-3, CA 125, and PSA for adults and geriatrics in Taita-Taveta County, Kenya, using the CLSI CA28-A3 guideline. This prospective cross-sectional study involved 244 healthy referents, including 124 females and 120 males of ages 50–95, between May 2015 and December 2017 at the Department of Clinical Chemistry of Moi Subcounty Hospital, Voi, Kenya. Serum CA 19-9, CEA, CA 15-3, CA 125, and PSA of the 244 referents were measured using a well-calibrated, quality controlled Clinical Chemistry AutoAnalyzer. Gender differences in the measured values of the biomarkers were assessed using the Mann-Whitney U test, while age differences were assessed using the Kruskal-Wallis H test followed by the Mann-Whitney U test with an adjusted significant ρ-value of less than 0.0167. Reference interval limits for the measured cancer biomarkers were expressed in terms of medians and ranged between 2.5 and 97.5 percentiles. The established 95% reference interval limits were: 0-58 U/mL males and 0-42.8 U/mL females for CA 19–9, 0–7 ng/mL for CEA, 0-56.9 U/mL for CA 15–3, 0–25 ng/mL for CA 125, and 0–6.8 ng/mL for PSA. Gender-related biomarker values were developed for CA 19-9 adults and geriatrics (60–70 years), CEA for geriatrics (60–70 years), and CA 15-3 for adults. Age-related biomarker values were developed for CA 19–9 males and not for females. In conclusion, gender-related 95% reference interval limits were developed for CA 19-9, CEA, CA 15-3, CA 125, and PSA, and age-related 95% reference interval limits were established for CA 19-9. CA 19-9 decreased from adulthood to the early elderly and increased in the more elderly population. These developed reference interval limits for these biomarkers, which differed from those reported in previous literature, could be adopted for use in Taita-Taveta County, Kenya, for better medical care. Doi: 10.28991/SciMedJ-2022-04-02-04 Full Text: PDF

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Reference interval limits for thyronine (TSH), thyroxine (T4) and triiodothyronine (T3) for geriatrics of the world including those of geriatrics of Taita-Taveta County, Kenya are limited. The aim of this study was to develop the 95% reference interval limits for thyronine (TSH), total thyroxine (T4), and total triiodothyronine (T3) for adults and geriatrics of Taita-Taveta County, Kenya. Two hundred and forty four referent individual randomly recruited from the four sub-county of Taita Taveta (Mwatate, Wundanyi, Voi and Taveta) County, Kenya participated in this reference interval limits development study. These referents had no history of thyroid gland diseases, were not on medication for thyroid diseases, and medications that affect the hypothalamus-pituitary-thyroid gland axis. These referents were free from HIV/ AIDS, syphilis, hepatitis B and C, and pregnancy. The serum used for the measurement of thyronin (TSH), total tetraiodothyronine (thyroxine [T4]) and triiodothyronine (T3) was obtained from blood which had been drawn from the vein of the 244 referent participants between 7-10 am after 8 to 12 hours of fasting recruited between May 2015 and December 2017. TSH, T4 and T3 were measured on a quality controlled calibrated Chemwell Auto-Analyzer machine using the principle that combines an enzyme immunoassay sandwich method with a final fluorescent detection (enzyme linked fluorescent assay (ELFA)

Fasting lipid profiles are affected by many factors including age, sex, geographical location, dietary habits (foods taken), life-style (sedentary or active, smoker or non-smoker, alcoholic or non-alcoholic), health status, environment, comprehensiveness of the selection criteria of the referent individual, socioeconomic status of the referent individual, racial differences, genetics, and the method and reagents used to estimate the lipid profile analyte of interest. The aim of the study is therefore to establish age and sex specific fasting lipid profile reference interval limits for adults and geriatrics of Taita-Taveta County, Kenya and compare them with those previously reported in medical literature. This was a prospective cross-sectional study design involving 272 randomly sampled healthy adults and geriatrics consisting of 123 males and 148 females. The study followed CLSI EP28 A3c guidelines. Fasting blood samples were collected from 272 adults and geriatrics referent individuals from Taita-Taveta County, Kenya and analyzed using a Clinical Chemistry Auto Analyzer (Integra 400) for total cholesterol (T-Chol), higher density lipoprotein cholesterol (HDL-Chol), low density lipoprotein cholesterol (LDL-Chol), non-high density lipoprotein cholesterol (non-HDL-Chol), triacylglycerols (TG), total cholesterol (T-Chol): high density lipoprotein cholesterol (HDL-Chol) ratio, triacylglycerols (TG): high density lipoprotein cholesterol (HDL-Chol) ratio, and low density lipoprotein cholesterol (LDL-Chol): high density lipoprotein cholesterol (HDL-Chol) ratio. Non-parametric analytical tools were used to establish the 2.5 percentile and 97.5 percentile reference interval based on gender and age. The established reference intervals for fasting lipid profiles were gender dependent for high density lipoprotein cholesterol, total cholesterol: high density lipoprotein cholesterol ratio and triacylglycerol (TG): high density lipoprotein cholesterol (HDL-Chol) ratio, gender independent for total cholesterol, low density lipoprotein cholesterol (LDH-Chol), triacylglycerols (TG), non-high density lipoprotein cholesterol (non-HDL-Chol), and low density lipoprotein cholesterol (LDL-Chol): high density lipoprotein cholesterol (HDL-Chol) ratio and were different from those reported in medical literature. In conclusion, the established age and gender specific reference intervals for fasting lipid profiles for adults and geriatrics of Taita-Taveta County, Kenya should be adopted for improved diagnostic interpretation and decision making by clinicians.