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Global sensitivity analysis of a model simulating an individual’s health state through their lifetime

  1. Abbygail Jaccard  Is a corresponding author
  2. Lise Retat  Is a corresponding author
  3. Martin Brown  Is a corresponding author
  4. Laura Webber  Is a corresponding author
  5. Zaid Chalabi  Is a corresponding author
  1. UK Health Forum, United Kingdom
  2. Department of Public Health, Environments and Society, London School of Hygiene and Tropical Medicine, United Kingdom
Research article
Volume 11(3) Winter 2018
Cite this article as: A. Jaccard, L. Retat, M. Brown, L. Webber, Z. Chalabi; 2018; Global sensitivity analysis of a model simulating an individual’s health state through their lifetime; International Journal of Microsimulation; 11(3); 100-121. doi: 10.34196/ijm.00190
6 figures and 7 tables

Figures

Figure 1
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Schematic of the individual-based chronic disease model used to simulate individuals through time.

Source: The figure has been adapted from Lymer et al. (2016).

Figure 2
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A graphical illustration of the first-order Sobol indices for each model input parameter: BMI, relative risk of stroke and relative risk of colorectal cancer for disease-free life expectancy.
Figure 3
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A graphical illustration of the first-order Sobol indices for each model input parameter: BMI, relative risk of stroke and relative risk of colorectal cancer for life expectancy.
Figure 4
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A graphical illustration of the first-order Sobol indices for each model input parameter: BMI, relative risk of stroke and relative risk of colorectal cancer for quality-adjusted life year.
Figure B.1
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A graph illustrating the relationship between the RR for stroke and BMI for males for two different age groups.

Notes: Both plots were fitted with a linear equation.

Figure B.2
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A graph illustrating the relationship between the RR for colorectal cancer and BMI for males for two different age groups.

Notes: Both plots were fitted with a linear equation.

Tables

Table 1
Summary of the BMI model parameters and their variances used in the sensitivity analysis.
Model parameter Mean Standard deviation Lower bound Upper bound
Healthy weight BMI probability (BMI < 25 kg/m2) 0.252 0.078 0.117 0.387
Overweight BMI probability (25 ≤ BMI < 30 kg/m2) 0.314 0.083 0.170 0.459
Obese BMI probability (BMI ≥ 30 kg/m2) 0.434 0.107 0.248 0.619
Mean BMI category probability 0.333 0.090 0.177 0.490
Mean BMI1 level 25.192 20.591 27.028
Case study 1 BMI level 27.5 22.899 29.336
Case study 2 BMI level 37.5 35.207 41.644
Table 2
Summary of the relative risk model parameters and their variances used in the sensitivity analysis.
Model parameter Mean Standard deviation Lower bound Upper bound
Relative risk stroke for overweight 1.213 0.056 1.116 1.310
Relative risk stroke for obese 1.758 0.107 1.573 1.944
Relative risk colorectal cancer overweight for 1.231 0.082 1.089 1.373
Relative risk colorectal cancer obese for 1.823 0.224 1.435 2.211
Table 3
Scalar additives z1, z2 and z3 sampled by PSUADE.
PSUADE parameter Lower bound for overweight Upper bound for overweight Lower bound for obese Upper bound for obese
z1 22.899 29.336 35.207 41.644
z2 1.116 1.310 1.573 1.944
z3 1.089 1.373 1.435 2.211
Table 4
Summary of the mean, standard deviation and variance for the disease-free life expectancy for the two case studies.
Case study Mean (years) Standard deviation (years) Variance (years2)
Overweight male 63.47 3.41 11.59
Obese male 48.32 3.14 9.87
Table 5
Summary of the mean, standard deviation and variance for the life expectancy for the two case studies.
Case study Mean (years) Standard deviation (years) Variance (years2)
Overweight male 79.76 0.11 0.01
Obese male 79.17 0.31 0.09
Table 6

Summary of the mean, standard deviation and variance for the quality-adjusted life years for the two case studies.

Case study Mean (years) Standard deviation (years) Variance (years2)
Overweight male 75.09 1.01 1.02
Obese male 70.06 1.06 1.12
Table C.1
Description of the categories used for the RF BMI.
Risk factor (RF) Number of categories (N) Categories
BMI 3 BMI < 25 kg/m2 (normal weight)
BMI from 25 to 29.99 kg/m-2 (overweight)
BMI ≥ 30 kg/m2 (obesity)

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