GAP Model

In the absence of effective treatments, the prognosis of idiopathic pulmonary fibrosis (IPF) has been very poor, with a median survival after diagnosis from 2 to 3 years based on several longitudinal studies.^1-4

Nonetheless, among individual patients there is wide heterogeneity.⁵ Some patients have an accelerated decline and die within months of diagnosis while many experience a slow, gradual progression over many years.⁵ This inherent uncertainty in prognosis may be frustrating to physicians who would like to provide patients with appropriate counseling in terms of life planning, treatment, and timely referral to lung transplant centers.⁶

In recent years, risk assessment systems for IPF have been developed.⁶ The baseline "GAP model" (so called for the variables it uses, Gender, Age, and Physiology) consists of 2 complementary prognostic tools that provide physicians with a framework for discussing prognosis and evaluating stage-specific management options with patients. The first GAP index and staging system provides a simple screening method to determine the average risk of mortality of patients with IPF by GAP stage.

The second, the GAP calculator, provides an estimation of risk of mortality for those patients in whom a more precise estimation of risk may change management. The most recent addition to this series of models, the longitudinal GAP model, includes 2 additional variables which significantly improved the discriminative performance of the model: a history of respiratory hospitalization and 24-week change in FVC.⁷

METHODS

To create the original GAP index and staging system, Ley et al⁶ used the records of 228 patients with IPF enrolled in the University of California, San Francisco, Interstitial Lung Disease Program’s longitudinal cohort study between 2001 and 2010 as a derivation cohort to develop the model.

Then 330 patients entered in the Mayo Clinic at Rochester (Rochester, Minnesota) (n=208) and the Morgagni-Pierantoni Hospital (Forli, Italy) (n=122) databases between 2000 and 2010 were used as a validation cohort. By using competing-risks regression modeling, potential predictors of mortality were retrospectively screened.

Potential predictor variables were required to be commonly measured and available at the time of initial consultation. Those considered included sex, body mass index, smoking status (those who had ever smoked versus those who had never smoked), use of long-term oxygen therapy, FVC, FEV₁, total lung capacity, and DLCO (corrected for hemoglobin level when available).

RESULTS

POINT-SCORE MODEL (GAP INDEX)

Model screening selected 4 predictors and points were assigned to variable categories to create a point-score model (the GAP index) (Table 1).⁶ Then, total point scores were grouped into 3 stages (the GAP staging system) (Table 2).⁶

Table 1.

The GAP index. Adapted from Ley B, et al. Ann Intern Med. 2012;156:684-691.⁶

DL_CO, diffusing capacity for carbon monoxide; FVC, forced vital capacity; GAP, gender, age, and lung physiology variables (FVC and DL_CO).

Table 2.

The GAP staging system. Adapted from Ley B, et al. Ann Intern Med. 2012;156:684-691.⁶

In order to obtain a total point score (range, 0–8), points are assigned for each variable of the scoring system.⁶ DL_CO should be corrected for hemoglobin level when available. If patients’ symptoms or lung function prohibits performance of the DL_CO maneuver, they should be scored in the “Cannot perform” category for DL_CO. The model cannot be applied if DL_CO results are not available because it was not done or not completed because of non-respiratory restrictions. The total point score is used to classify patients as stage I (0–3 points), stage II (4–5 points), or stage III (6–8 points). Table 2 lists model-predicted 1-, 2-, and 3-year mortality by stage.

Longitudinal GAP Model

Recently, Ley and colleagues published an update to the GAP model to include longitudinal variables.⁷ Of the variables investigated, a history of respiratory hospitalization and 24-week change in FVC significantly improved the predictive performance of the GAP model. Similar to the original GAP model,⁶ points are assigned for each variable of the scoring system to obtain a total point score (Table 3).⁷ The total point score is then used to estimate mortality risk for that particular patient (Table 4).

Table 3.

The longitudinal GAP categorical and point index models. Adapted from Ley B, et al. Eur Respir J. 2015;45:1374-1381.⁷

DL_CO, diffusing capacity for carbon monoxide; FVC, forced vital capacity; GAP, gender, age, and lung physiology variables (FVC and DL_CO); HR, hazard ratio.

Table 4.

The longitudinal GAP point index models: predicted 1- and 2-year mortality risks. Adapted from Ley B, et al. Eur Respir J. 2015;45:1374-1381.⁷

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