Biological Variation: a practical review - QCNet

1 Biological Variation: a practical review Carmen Ric s Brussels & Amsterdam 2010 Bio-Rad_QC Seminars C Ric s 2010 QC Seminars Within-subject Biological variation Age, sex Diet, physic exercise Pathology, treatment Within-day variation, season variation Homeostasis Fraser CG. Biological Variation: from theory to practice. AACC press, 2001. C Ric s 2010 QC Seminars Within-subject Biological variation Fluctuation of the concentration of blody fluid components around the setting point Fraser CG. Biological Variation: from theory to practice. AACC press, 2001. C Ric s 2010 QC Seminars Between-subject Biological variation Differences in concentration of the components of biologic fluids among persons Fraser CG. Biological Variation: from theory to practice. AACC press, 2001. C Ric s 2010 QC Seminars How to estimate the components of BV.

2 1. To obtain n samples from m healthy volunteers n, m and sampling interval are irrelevant Key factors: sample obtention and maintenance Fraser CG. Biological Variation: from theory to practice. AACC press, 2001. C Ric s 2010 QC Seminars How to estimate the components of BV. 2. To eliminate outliers Cochran test outlier values Reed test outlier individuals Ric s C et al. Clin Chem 1994;40:472-477. C Ric s 2010 QC Seminars How to estimate the components of BV. 3. To applicate the ANOVA test sI2 =s (W+A)2 sA2. sG2 = stotal2 sI2 M1 M2 M3 Var within- subject S1 Var s1. S2 Var s2. S3 Var s3. S4 Var s4. S(W+A)2. Ric s C et al. Clin Chem 1994;40:472-477. C Ric s 2010 QC Seminars Compilation of data on Biological variation Ross JW. Handbook of clinical chemistry. Boca Raton: CRC press, 1982:391-42. Fraser CG. Arch Pathol Lab Med 1988;112:404-15.

3 Fraser CG. Arch Pathol Lab Med 1992;116:916-23. Sebasti n-Gambaro et al. Eur J Clin Chem Clin Biochem 1997;35:845-52. C Ric s 2010 QC Seminars What else? a DATABASE. selective permanently updated C Ric s 2010 QC Seminars Why? To give information on quality specifications for Imprecision (CV,%). Bias (SE,%). Total error (TE,%). C Ric s 2010 QC Seminars Material 1. PAPERS SEARCH: BIOS, CURRENT CONTENTS, EMBASE, MEDLINE, PUBMED. 2. CLASSIFICATION of the information obtained - BV components CVW, CVG. - Calculations Individuality, Critical differences - Descriptions N, days, samples - Observations Health status, fasting C Ric s 2010 QC Seminars Method (1). 1. EXCLUSSIONS. Papers with too high analytical variation (CVA> CVW). Papers not specifically designed to estimate CVW. and CVG. Studies made within a day Studies made on non-healthy subjects C Ric s 2010 QC Seminars Method (2).

4 2. EXPRESSION (for each analyte). Papers in ascending order according to the CVW. Search for relationships between CVW and number of subjects, sex, health status, fasting;. number of samples per subject, time span of the study . If no relationships are observed: calculation of the median of CVW and CVG values from all papers compiled C Ric s 2010 QC Seminars Example: s- Glucose CVW CVG CVA N Td Ss Mean Unit Year 40 28 3 mmol/L 1994. 27 140 10 1989. 14 70 10 1988. 20 365 12 1989. 68 112 11 94 mg/dL 1970. 48 365 12 140 2002. 9 70 10 94 1971. 1105 60 9 mmol/L 1978. 10 5 5 1986. NC 126 180 6 1985. 10 5 5 1993. NC 148 180 6 1985. C Ric s 2010 QC Seminars Method (3). 3. CALCULATION OF SPECIFICATIONS. CVA(%) < CVW. SEA (%) < (CVW2 + CVG2)1/2. TEA (%) < *CVA + SEA. - Elevitch FR editor. AP Conference II. Skokie IL 1976.

5 - Gowans EMSs et al. Scan J Clin Lab Invest 1988;48:757-764. - Fraser CG et al. Scand J Clin Lab Invest 1993; 53 suppl 212:8-9. C Ric s 2010 QC Seminars Results (Database, 2010 update). 319 analytes 213 papers (12 rejected). 182 authors (>15 countries). 59 journals C Ric s 2010 QC Seminars Database 2010 update Example Analyte Biological Desirable Variation Specifications CVW CVG CV(%) SE(%) TE(%). Srm- -Amilase 8,7 28,3 4,4 7,4 14,6. Srm- -Amilasa, pancreatic 11,7 29,9 5,9 8,0 17,7. Srm- -Carotene 35,8 65,0 17,9 18,6 48,1. Srm- -Fetoprotein 12,0 46,0 6,0 11,9 21,8. Srm- -Tocoferol 13,8 15,0 6,9 5,1 16,5. C Ric s 2010 QC Seminars Database 2010 update References http:// www. http:// www. C Ric s 2010 QC Seminars Database - contras Discrepancies among authors in some analytes (hormones). A single paper available for 90.

6 Analytes Many analytes not studied C Ric s 2010 QC Seminars Database - pros Wide source of information Papers poorly reliable have been disegarded C Ric s 2010 QC Seminars Database - Applications Quality specifications Delta check Reference change value C Ric s 2010 QC Seminars Quality specifications Stockholm international consensus 1999. Effect on clinical outcome Effect on general clinic decisions Professional recommendations Regulatory bodies / EQAS proposals Current state of the art Hyltoft P et al. Strategies to set global analytical quality specifications in laboratory medicine. Scand J Clin Lab Invest 1999;57,7. C Ric s 2010 QC Seminars Use of Q specifications 1. To design internal control rule To calculate the critical error increase CE = TEA / 1,96 CVA. To select the control procedure CE Rule Controls/run 1:2s N=2.

7 <2 1:2,5s N=4. 1:3s N=6. 1:2s N=1. (2-3) 1:3 N=2. 1:3,5s N=4. 1;2,5s N=1. >3 1:3s N=2. 1:3,5s N=4. Hyltoft P et al. Strategies to set global analytical quality specifications in laboratory medicine. Scand J Clin Lab Invest 1999;57,7. C Ric s 2010 QC Seminars Use of Q specifications 2. to evaluate internal QC results C Ric s 2010 QC Seminars Use of Q specifications 3. to evaluate EQA results C Ric s 2010 QC Seminars Use of Q specifications 3. to evaluate EQA results - SEQC. C Ric s 2010 QC Seminars Use of Q specifications 3. to evaluate EQA results - SEQC. % of results reaching specifications based on BV. C Ric s 2010 QC Seminars Delta Check Check < 2 * Zp (CVA2 +CVW2) . Z = significant autovalidation Z = highly significant manual verification Fraser CG. Accred & Qual Assur 2002;7:455-460. C Ric s 2010 QC Seminars Reference change value Difference between two consecutive results that may indicate a change in the patient health state Fraser CG.

8 Biological variation: from principles to practice. Washington DC. AACC Press ,2001. C Ric s 2010 QC Seminars Reference change value SOULD BE USED. For analytes with high individuality CVI/CVG< Fraser CG. Biological variation: from principles to practice. Washington DC. AACC Press ,2001. C Ric s 2010 QC Seminars Reference change value SHOULD BE USED. In 276 of the 319 analytes from the current database C Ric s 2010 QC Seminars Reference change value RCV = 21/2*Zp*(CVA2 + CVW2)1/2. RCV = * (CVA2 + CVW2)1/2. Fraser CG. Biological variation: from principles to practice. Washington DC. AACC Press ,2001. C Ric s 2010 QC Seminars Reference change vlaue Interpreting resultas of analytes with highindividuality Fraser CG. Biological variation: from principles to practice. Washington DC. AACC Press ,2001. C Ric s 2010 QC Seminars Reference change value - reporting NINEWELLS HOSPITAL AND MEDICAL SCHOOL.

9 Result Units Ref. values Sodium 138 * mmol/L 135-147. Potassium mmol/L Urea ** mmol/L Creatinine 137 > mmol/L 50-100. Bilirubins 100 >> mmol/L NAME. Albumin 23 << g/L 36-50. Calcium ** mmol/L Fraser CG. Biological Variation: From Principles to Practice. Washington, DC, AACC Press, 2001. C Ric s 2010 QC Seminars Reference change value - in pathology Pathology Analyte CVI (%). Cancer ovarium CA 125 46. Cancer mamarian CA 17. C. colorectal CEA 45. Diabetes HbA1C 9. mellitus Microalbumin 36. Hepatic disease -fetoprotein 40. Paget Alkaline phos. 12. Ric s C et al. Ann Clin Biochem 2007; 44: 343 352. Reference change value - two analytes combined VRC combinado 100. Uratos Diferencias (%). 50. 0. -50. -100. -100 -50 0 50 100 150. Creatinina Diferencias (%). estables obstructiva toxicidad FK506. infecci n citomegalovirus rechazo agudo Biosca C.

10 Clin Chem 2001;47:2146-8. C Ric s 2010 QC Seminars References (1). Fraser CG. Biological Variation: From Principles to Practice. AACC Press, Washington DC, 2001. Ric s C, lvarez V, Cava F, Garc a-Lario JV et al. Current databases on Biological variation: pros,cons and progress. Scand J Clin Lab Invest 2004; 64: 175 84. Ric s C, Iglesias N, Garc a-Lario JV, Sim n M et al. Within- subject Biological variation in disease: collated data and clinical consequences. Ann Clin Biochem 2007; 44: 343 352 . Biosca C, Ric s C, Jim nez CV, Lauzurica R et al. Are equally spaced specimen collections necessary to assess Biological variation?. Evidence from renal transplant recipients. Clin Chim Acta 2000;301:79-85. C Ric s 2010 QC Seminars References (2). Hyltoft Petersen P, Sandberg S, Fraser CG, Goldsmith H. Influence of index of individuality on false positives in repeated sampling from healthy individuals.