ABSTRACT
Conclusion:
We suggest to use RCV as well as to use population-based reference interval. RCV could be a valuable tool for clinical decision in especially monitoring individuals
Results:
RCVs (Z=1.96) of these analytes were calculated as 44.30% for cortisol, 31.25% for DHEA-S, 64.34% for estradiol, 35.14% for FSH, 64.58% for LH, 65.24% for prolactin, 27.28% for total testosterone, 39.24% for troponin I, 29.00% for NT-proBNP, 71.93% for PTH, 59.22% for insulin, 40.51% for ferritin, 68.04% for folate, 53.74% for TSH, 23.07% for free T3, 17.38% for free T4, 29.27% for anti TG, 42.52% for anti TPO, 35.42% for AFP, 21.58% for CA 15-3, 44.99% for CA 19-9, 68.92% for CA 125, 36.83% for CEA and 51.00% for total PSA
Methods:
Twenty four serum analytes (cortisol, DHEA-S, estradiol, follicle stimulating hormone (FSH), luteinizing hormone (LH), prolactin, testosterone, troponin I, NT-proBNP, parathormone (PTH), insulin, ferritin, folate, thyroid stimulating hormone (TSH), free T3, free T4, thyroglobulin antibody (anti TG), thyroid peroxidase antibody (anti TPO), alpha fetoprotein (AFP), CA 15-3, CA 19-9, CA 125, carcinoembryonic antigen (CEA) and total PSA) were analyzed with Roche kits (Roche Diagnostics, Mannheim, Germany), which were manifactured to use immun analyzer Cobas ®6000 (Roche Diagnostics, Mannheim, Germany). We used analytic coefficient of variation (CVa) from internal quality control programme. Intra-individual biological variation (CVw) were obtained from Ricos current updated published in Westgards website. This database was updated in 2014. We calculated RCV using this formula RCV=21/2xZx(CVa2+CVw2)1/2 (Z=1.65, 95% probability, unidirectional; Z=2.33, 99% probability, unidirectional; Z=1.96, 95% probability, bidirectional; Z=2.58, 99% probability, bidirectional).
Objective:
The use of reference change values (RCV) has been advocated as a most appropriate for monitoring individuals in clinical laboratories. The aim of this study was to calculate of RCV of 24 analytes of immun analysis parameters