Chest
Volume 124, Issue 3, September 2003, Pages 922-928
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Clinical Investigations
SARCOIDOSIS
Predicting Mortality in Patients With Sarcoidosis Awaiting Lung Transplantation

https://doi.org/10.1016/S0012-3692(15)37649-2Get rights and content

Objectives:

To identify factors associated with mortality in patients with sarcoidosis listed for lung transplantation, and to create a model for predicting intermediate-term mortality in these individuals.

Design:

Retrospective cohort study of patients with sarcoidosis listed for lung transplant in the United States between 1995 and 2000. After identifying important risk factors for death, we developed a mortality prediction model based on an inception cohort of 75% of the subjects. The remaining 25% of the individuals served as a validation cohort for determining the validity of the model.

Setting and patients:

All patients with sarcoidosis in the United States irrespective of referral center listed for lung transplantation between 1995 and 2000.

Measurements and main results:

Adequate follow-up data were available for 405 patients, and 111 patients (27.4%) died while awaiting lung transplantation. Neither patient age nor gender correlated with mortality. Survivors and nonsurvivors did not differ based on the results of spirometric testing. African Americans faced a significantly increased risk of death, which persisted after controlling for other confounders (odds ratio, 2.5). The amount of supplemental oxygen used and the mean pulmonary artery pressure were the only other variables predictive of mortality. The mean (± SD) pulmonary artery pressure in those who survived was 31.7 ± 11.5 mm Hg, compared to 41.4 ± 14.4 mm Hg in nonsurvivors (p < 0.01). Survivors required 2.2 ± 2.0 L/min of oxygen vs 2.9 ± 1.7 L/min in those who died awaiting transplant (p < 0.01). Differences in pulmonary artery pressures did not reflect differences in cardiac status, as the pulmonary capillary wedge pressure and the cardiac index were similar in survivors and nonsurvivors. The final mortality prediction model included three variables: race, amount of supplemental oxygen needed, and mean pulmonary artery pressure. Based on the validation cohort, the concordance of the model for death within 2 years of listing was 0.61 (95% confidence interval, 0.47 to 0.76), indicating only moderate explanatory power.

Conclusions:

Race, pulmonary hypertension, and oxygen use are important factors indicative of mortality in this population. Specific guidelines for determining time of referral for transplantation in advanced sarcoidosis should be developed. Recommendations extrapolated from data for other types of interstitial lung disease may not be applicable in sarcoidosis. The independent effect of race on outcome is troubling.

Section snippets

Subjects and End Points

The United Network for Organ Sharing (UNOS) maintains a registry of all patients listed for organ transplantation in the United States. We reviewed this registry and identified all persons with a diagnosis of sarcoidosis who were on the OLT list between January 1995 and December 2000, regardless of initial listing date. The diagnosis of sarcoidosis was based on the reports of the referring transplant centers. Patients listed for any form of possible OLT (single lung, bilateral lung, or

Results

During the study period, 12,228 patients in the United States were listed with the UNOS for OLT. Of these, 427 cases were for sarcoidosis, and data were available for 405 persons (94.8%). The mortality rate while awaiting OLT was 27.4%.

As shown in Table 1, neither age nor gender differed between those who survived and those who died while on the transplant list. For example, the mean age of survivors was 45.6 ± 8.7 years, as compared to 44.7 ± 8.1 year for nonsurvivors (p = 0.47). Similarly,

Discussion

This effort at developing a mortality prediction model for subjects with sarcoidosis demonstrates that three variables routinely available to clinicians at time of listing correlate with the probability of death. Two of these factors, race and need for supplemental oxygen, can be determined easily. Nonetheless, the predictive model had only fair validity. In other words, data available at one static time point have power at predicting future outcomes (which may be as long a 2 years away) but

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