AGE BASED PREDICTION BIAS IN SPIROMETRY REFERENCE EQUATIONS

1. AGE BASED PREDICTION BIAS IN SPIROMETRY REFERENCE EQUATIONS C Maatoug, K Hadj Mabrouk, H Thabet, S Amimi, Srouatbi, H Ben Saad. Groupement du Médecine du Travail du Gouvernorat de Sousse INTRODUCTION Age and height are the most important explanatory variables in spirometry reference equations. Guidelines for the measurement of spirometric indices, aiming to maximise accuracy and precision, focus on equipment, measurement procedures and quality control. They do not, however, address the equally important issues of accurate age measurement. For example in the Global Lungs dataset [1] 45% of ages were recorded in whole years, many rounded by software. This has the potential to bias the prediction. . AIM To address one question, focussing on spirometric data (forced expiratory volume (FEV1), forced vital capacity (FVC), FEV1/FVC ratio, and forced expiratory flow when x% of FVC has been exhaled (FEFx%FVC)) in adults Tunisian. How large is the prediction bias due to biases in age recording? Data: we used data on 38 adults Tunisian: 19 healthy lifelong non-smokers (8 males/11 females) and 19 smokers (12 males/7 females) POPULATION AND METHODS Spirometry measurements: done according recent international guidelines (ATS/ERS 2005). Applied spirometric reference values: local reference equations [2, 3]. Predicted values were calculated using height (cm) and age in years recorded to at least 1 decimal accuracy for age. The effects on predicted values of using whole-year age versus decimal age were quantified by 2 ways: i)variable predicted = 100 x predicted value calculated using age (decimal year minus whole year) ii) variable measured/predicted = measured spirometric variable expressed as a percentage of the predicted value calculated using age (decimal year minus whole year). i) Using age in whole years rather than decimal age introduced biases with a  variable predicted varying between -1.3 and -1.9. ii) The  variable measured/predicted was varied between 0.30 and 0.56. RESULTS 4. Pièges a éviter CONCLUSION Recording age accurately reduces bias further. References 1. Quanjer PH et al. Multi-ethnic reference values for spirometry for the 3-95 year age range. Report of the Global Lungs Initiative, ERS Task Force to establish improved Lung Function Reference Values. ERJ Express. Published on June 27, 2012 as doi: 10.1183/09031936.00080312. 2. Tabka Z et al. Spirometric reference values in a Tunisian population. Tunis Med 1995;73:125-31. 3. Ben Saad H et al. Vital capacity and peak expiratory flow rates in a North-African population aged 60 years and over. Rev Mal Respir 2003;20:521-30.