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Table 7 Quality Assessment of Modelling Study (Flaherman 2007 [31])

From: Recommendations for the screening of paediatric latent tuberculosis infection in indigenous communities: a systematic review of screening strategies among high-risk groups in low-incidence countries

Criteriaa Criteria met? (1 = yes,
x = no or not reported)
 Inputs and outputs relevant to the decision-making perspective 1
 Structure consistent with the theory of the disease in question 1
 Structure as simple, although including essential aspects for decision-making. Simplifications, if any, justified as not significantly affecting the results. 1
 Heterogeneity in the modelled population accounted for by stratifying by groups that have different outcome probabilities or costs. 1
 Time horizon of the model sufficient to detect important (and clinically meaningful) differences in long-term health and cost outcomes. 1
 Data identification:
  Systematic reviews of the literature conducted on key model inputs. x
  Ranges provided in base-case estimates of all input parameters for which sensitivity analyses were done. 1
  Data based on expert opinion, if used, are derived via formal methods, e.g. Delphi x
  Attempts to obtain new data prior to modeling have been considered. x
 Data modeling:
  Modeling methods follow accepted methods of biostatistics and epidemiology. 1
 Data incorporation:
  Use of either probabilistic (Monte Carlo, first-order) simulation or deterministic (cohort) simulation 1
  Included sensitivity analyses of key parameters. 1
 Internal validation:
  Model subjected to internal testing through input of extreme values (or equal values for replication testing) x
  Calibration data, where available, should be from sources independent of those used to estimate inputs x
  Source code available for peer-review. x
 Between-model validation:
  Models developed independently of each other, to allow convergent validity testing x
  Significant discrepancies in model outputs compared to other published results explained 1
 External and predictive validation:
  Model based on the best evidence available at the time 1
 Total Score (out of 18) 11
  1. aBased on the ISPOR Principles of Good Practice for Decision Analytic Modeling in Health-Care Evaluation [18]. (Since this study did not employ a transition-state model, components of the ISPOR guidelines pertaining to such models were excluded from this assessment)