How Glaucoma Patients Assess Different      Aspects of Their Treatment? An Elicitation of Patients’ Preferences by    Anal...
Weighting treatment aspects         Rationale: Why calculate weights? Patients weight different treatment aspects accordi...
AHP                 Rationale: Why AHP?Patient preferences as a basis for weighting treatment aspects      elicit prefere...
Objective of the AHP  To weigh the different aspects of glaucoma   treatment by eliciting the preferences of patients   w...
Background The mathematician Thomas L. SAATY developed the AHP  procedure in the early 1970th as a technique to solve  mu...
Hierarchical Structure of the AHP                                                      Decision Problem                   ...
How the AHP works  Pairwise comparisons of criteria are used to elicit the   relative importance of one criterion in comp...
AHP scale used in pairwise comparisons   How much more important is criterion A in    comparison to criterion B?         9...
AHP Matrix AHP matrix of pairwise comparisons                  A                 B                C         A        1    ...
Mathematical conditions on the AHP structure 1) Completeness of criteria  a complete set of criteria    should be assesse...
Prerequisites The preferences of individuals should correspond to the following prerequisites 1) Reciprocity         if A...
Calculation of the right “Eigenvector” (I)Pairwise comparison matrix A; relative weights w1, w2 und w3of the compared elem...
Calculation of the right “Eigenvector” (II)This relation is described by the following equation:              A x W = n x ...
Calculation of the right “Eigenvector” (III)This transforms the equation to:             A* x W* = λmax x W*with A* = pair...
Inconsistency Is measured by the so called Consistency Ratio (CR) Is checking for the „logic“ of the particular pairwise...
Inconsistent judgments                 A>B>C>APage 16    © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
Patient samplen     N = 7 Pretest => Language abilities, Cognition, Proxiesn     N = 25 Patientsn     Setting: Ophthalmolo...
Patients’ characteristics N = 25 Study; 68,3±13,3 years; €€8 •17; first diagnosis 1 – 21 years Glaucoma          Primar...
Assessed aspects Reading and seeing detail Peripheral vision Darkness and glare Autonomy subdivided in:       househo...
Example: Questionnaire different side effects Page 20        © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
EQ-5D VAS  21Page 21     © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
Inconsistency = 0.04                                                                         Inconsistency                ...
Results                                                  weight, mean, sd, CI95% Reading and seeing detail 0.229, 0.212 ±...
Stratified population comparisonAutonomyReading detailsDarkness & GlarePeripheral visionSide effectsTreatment burden...
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How Glaucoma Patients Assess Different Aspects of Their Treatment? An Elicitation of Patients’ Preferences by Analytic Hierarchy Process (AHP)

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How Glaucoma Patients Assess Different Aspects of Their Treatment?
An Elicitation of Patients’ Preferences by Analytic Hierarchy Process (AHP)

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How Glaucoma Patients Assess Different Aspects of Their Treatment? An Elicitation of Patients’ Preferences by Analytic Hierarchy Process (AHP)

  1. 1. How Glaucoma Patients Assess Different Aspects of Their Treatment? An Elicitation of Patients’ Preferences by Analytic Hierarchy Process (AHP)Dintsios CM / Scheibler FF / Janssen I / Gerber A / Finger R HTAi, Bilbao, June 25th 2012
  2. 2. Weighting treatment aspects Rationale: Why calculate weights? Patients weight different treatment aspects according to their preferences  Patients’ preferences These aspects may serve as patient-relevant measures (endpoints) in HTA  Patients’ involvement By weighting treatment aspects prioritization is based on patients’ views  Legitimating In benefit assessments or cost-effectiveness analyses the derived weights can be used for the aggregation of multiple (composite) endpoints  Endpoint aggregation…Page 2 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  3. 3. AHP Rationale: Why AHP?Patient preferences as a basis for weighting treatment aspects  elicit preferences via AHP  AHP is one method – others are available, e.g. Conjoint Ananlysis Page 3 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  4. 4. Objective of the AHP  To weigh the different aspects of glaucoma treatment by eliciting the preferences of patients with the AHP-procedure.  I.e. to estimate the „relative importance“ of treatment aspects, especially importance to patientsPage 4 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  5. 5. Background The mathematician Thomas L. SAATY developed the AHP procedure in the early 1970th as a technique to solve multicriteria decision problems How the procedure works:  Decision issues are structured hierarchically into different levels of criteria / alternatives.Page 5 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  6. 6. Hierarchical Structure of the AHP Decision Problem (which car do I want?) Criterium22 Criterion Criterium 1 Criterion 1 (e.g. gasoline ... Criteriumnn Criterion (e.g. colour) consumption) Criterium 1.1 ... ... Alternative 1 Alternative 2 ... Alternative n (Peugeot 206) (Golf)Page 6 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  7. 7. How the AHP works  Pairwise comparisons of criteria are used to elicit the relative importance of one criterion in comparison to the others  Mathematical procedure: based on matrices of pairwise comparisons weights are calculated for each criterion with the help of the „Eigenvector“- methodPage 7 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  8. 8. AHP scale used in pairwise comparisons How much more important is criterion A in comparison to criterion B? 9 7 5 3 1 3 5 7 9 A Equal importance B 1 - equally important 3 - slightly more important 5 - more important 7 - much more important 9 - extremely more importantPage 8 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  9. 9. AHP Matrix AHP matrix of pairwise comparisons A B C A 1 1/5 2 B 5 1 6 C 1/2 1/6 1Page 9 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  10. 10. Mathematical conditions on the AHP structure 1) Completeness of criteria  a complete set of criteria should be assessed 2) Independence of preference information  at the different levels of hierarchy 3) Independence of criteria  should be disjunct, exclude each other 4) Scale should be a relative scale  preferences measured on a common relative scalePage 10 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  11. 11. Prerequisites The preferences of individuals should correspond to the following prerequisites 1) Reciprocity  if A is 3 times more important than B, then B is 1/3 as important as A 2) Transitivity  if A >B and B>C then A>C 3) Consistency  resulting from reciprocity and transitivityPage 11 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  12. 12. Calculation of the right “Eigenvector” (I)Pairwise comparison matrix A; relative weights w1, w2 und w3of the compared elements are knownMultiply matrix A with the vector W of the weights: 3 x w1 3 x w2 3 x w3 This equates to the multiplication of the respective weightwith the number of the compared elements n Page 12 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  13. 13. Calculation of the right “Eigenvector” (II)This relation is described by the following equation: A x W = n x Wwith A = pairwise comparison matrix,W = vector of the weights, n = compared elementsIn Matrix Algebra: W = right „Eigenvector“ n = Eigen-value of matrix A In reality W is unknown and has to be approximated by aregression analysis approach Page 13 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  14. 14. Calculation of the right “Eigenvector” (III)This transforms the equation to: A* x W* = λmax x W*with A* = pairwise comparison matrix, W* = right Eigenvector ofmatrix A, λmax = maximal Eigen-value of matrix A*Basic assumption of AHP: the calculated right Eigenvector ofmatrix A equates approximately the vector of the relativeweights Page 14 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  15. 15. Inconsistency Is measured by the so called Consistency Ratio (CR) Is checking for the „logic“ of the particular pairwise comparison, (i. e. how consistent is the respective pairwise comparison with regard to all the other pairwise comparisons) According to SAATY a CR ≤ 0,1 is accepted and allows for the conclusion that the weights are derived on a consistent basis Page 15 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  16. 16. Inconsistent judgments A>B>C>APage 16 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  17. 17. Patient samplen N = 7 Pretest => Language abilities, Cognition, Proxiesn N = 25 Patientsn Setting: Ophthalmology ambulance at University of Bonnn Glaucoma patients: different manifestations and severitiesn AHP-Questionnairen Elicitation of utilities with EQ5D – VASn Stratification according to these utilitiesPage 17 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  18. 18. Patients’ characteristics N = 25 Study; 68,3±13,3 years; €€8 •17; first diagnosis 1 – 21 years Glaucoma  Primary chronic wide-angle glaucoma 55%  Narrow-angle (congestive) glaucoma 9%  Wide-angle glaucoma with narrow-angle component 9%  Normal-tension glaucoma 9%  Suspected glaucoma 18% visual acuity bad eye 0,59 ± 0,33 Tensio RE 17,2 ± 6,2; Tensio LE 18,1 ± 4,7 Glaucoma management +/- 82%/18% Page 18 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  19. 19. Assessed aspects Reading and seeing detail Peripheral vision Darkness and glare Autonomy subdivided in:  household chores  outdoor mobility Treatment-related patient’s burden Side effectsPage 19 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  20. 20. Example: Questionnaire different side effects Page 20 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  21. 21. EQ-5D VAS 21Page 21 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  22. 22. Inconsistency = 0.04 Inconsistency = 0.00 Inconsistency = 0.01Page 22 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  23. 23. Results weight, mean, sd, CI95% Reading and seeing detail 0.229, 0.212 ± 0.123, 0.161 - 0.263 Peripheral vision 0.089, 0.085 ± 0.058, 0.061 - 0.109 Darkness and glare 0.153, 0.165 ± 0.111, 0.119 - 0.211 Autonomy subdivided in: 0.394, 0.371 ± 0.145, 0.311 - 0.431  household chores 0.239, 0.275 ± 0.258, 0.168 - 0.381  outdoor mobility 0.761, 0.725 ± 0.258, 0.619 - 0.832 Treatment-related burden 0.047, 0.052 ± 0.050, 0.027 - 0.076 Side effects 0.088, 0.115 ± 0.131, 0.060 - 0.168 Utilities EQ-5D vs VAS (82.76 ± 22.21 vs. 65.64 ± 19.95, p = 0.003) Page 23 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  24. 24. Stratified population comparisonAutonomyReading detailsDarkness & GlarePeripheral visionSide effectsTreatment burden U > 80 (N = 7)AutonomyReading detailsDarkness & GlarePeripheral visionSide effectsTreatment burden U < 65 (N = 11)AutonomyReading detailsDarkness & GlarePeripheral visionSide effectsTreatment burden Page 24 © Dintsios | HTAi | Bilbao, June 25 th2012 | Glaucoma patients’
  25. 25. Thank you!
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