Identifying critically ill patients who may benefit from adjunctive corticosteroids: not as easy as we thought

Combining Prognostic and Predictive Enrichment Strategies to Identify Children With Septic Shock Responsive to Corticosteroids

OBJECTIVES

Prognostic and predictive enrichment strategies are fundamental tools of precision medicine. Identifying children with septic shock who may benefit from corticosteroids remains a challenge. We combined prognostic and predictive strategies to identify a pediatric septic shock subgroup responsive to corticosteroids.

DESIGN

We conducted a secondary analysis of 288 previously published pediatric subjects with septic shock. For prognostic enrichment, each study subject was assigned a baseline mortality probability using the pediatric sepsis biomarker risk model. For predictive enrichment, each study subject was allocated to one of two septic shock endotypes, based on a 100-gene signature reflecting adaptive immunity and glucocorticoid receptor signaling. The primary study endpoint was complicated course, defined as the persistence of two or more organ failures at day 7 of septic shock or 28-day mortality. We used logistic regression to test for an association between corticosteroids and complicated course within endotype.

MEASUREMENTS AND MAIN RESULTS

Among endotype B subjects at intermediate to high pediatric sepsis biomarker risk model-based risk of mortality, corticosteroids were independently associated with more than a 10-fold reduction in the risk of a complicated course (relative risk, 0.09; 95% CI, 0.01-0.54; p = 0.007).

CONCLUSIONS

A combination of prognostic and predictive strategies based on serum protein and messenger RNA biomarkers can identify a subgroup of children with septic shock who may be more likely to benefit from corticosteroids. Prospective validation of these strategies and the existence of this subgroup are warranted.

Glucocorticoid Receptor Polymorphisms and Outcomes in Pediatric Septic Shock

OBJECTIVE

Polymorphisms of the glucocorticoid receptor gene are associated with outcome and corticosteroid responsiveness among patients with inflammatory disorders. We conducted a candidate gene association study to test the hypothesis that these polymorphisms are associated with outcome and corticosteroid responsiveness among children with septic shock.

DESIGN

We genotyped 482 children with septic shock for the presence of two glucocorticoid receptor polymorphisms (rs56149945 and rs41423247) associated with increased sensitivity and one glucocorticoid receptor polymorphism (rs6198) associated with decreased sensitivity to corticosteroids. The primary outcome variable was complicated course, defined as 28-day mortality or the persistence of two or more organ failures 7 days after a septic shock diagnosis. We used logistic regression to test for an association between corticosteroid exposure and outcome, within genotype group, and adjusted for illness severity.

SETTING

Multiple PICUs in the United States.

INTERVENTIONS

Standard care.

MEASUREMENTS AND MAIN RESULTS

There were no differences in outcome when comparing the various genotype groups. Among patients homozygous for the wild-type glucocorticoid receptor allele, corticosteroids were independently associated with increased odds of complicated course (odds ratio, 2.30; 95% CI, 1.01-5.21; p = 0.047).

CONCLUSIONS

Based on these glucocorticoid receptor polymorphisms, we could not detect a beneficial effect of corticosteroids among any genotype group. Among children homozygous for the wild-type allele, corticosteroids were independently associated with increased odds of poor outcome.

Glucocorticoid Receptor Expression in Peripheral WBCs of Critically Ill Children

OBJECTIVES

To characterize glucocorticoid receptor expression in peripheral WBCs of critically ill children using flow cytometry.

DESIGN

Prospective observational cohort.

SETTING

A university-affiliated, tertiary PICU.

PATIENTS

Fifty-two critically ill children.

INTERVENTIONS

Samples collected for measurement of glucocorticoid receptor expression and parallel cortisol levels.

MEASUREMENTS AND MAIN RESULTS

Subjects with cardiovascular failure had significantly lower glucocorticoid receptor expression both in CD4 lymphocytes (mean fluorescence intensity, 522 [354-787] vs 830 [511-1,219]; p = 0.036) and CD8 lymphocytes (mean fluorescence intensity, 686 [350-835] vs 946 [558-1,511]; p = 0.019) compared with subjects without cardiovascular failure. Subjects in the upper 50th percentile of Pediatric Risk of Mortality III scores and organ failure also had significantly lower glucocorticoid receptor expression in CD4 and CD8 lymphocytes. There was no linear correlation between cortisol concentrations and glucocorticoid receptor expression.

CONCLUSIONS

Our study suggests that patients with shock and increased severity of illness have lower glucocorticoid receptor expression in CD4 and CD8 lymphocytes. Glucocorticoid receptor expression does not correlate well with cortisol levels. Future studies could focus on studying glucocorticoid receptor expression variability and isoform distribution in the pediatric critically ill population as well as on different strategies to optimize glucocorticoid response.

Developing a clinically feasible personalized medicine approach to pediatric septic shock

RATIONALE

Using microarray data, we previously identified gene expression-based subclasses of septic shock with important phenotypic differences. The subclass-defining genes correspond to adaptive immunity and glucocorticoid receptor signaling. Identifying the subclasses in real time has theranostic implications, given the potential for immune-enhancing therapies and controversies surrounding adjunctive corticosteroids for septic shock.

OBJECTIVES

To develop and validate a real-time subclassification method for septic shock.

METHODS

Gene expression data for the 100 subclass-defining genes were generated using a multiplex messenger RNA quantification platform (NanoString nCounter) and visualized using gene expression mosaics. Study subjects (n = 168) were allocated to the subclasses using computer-assisted image analysis and microarray-based reference mosaics. A gene expression score was calculated to reduce the gene expression patterns to a single metric. The method was tested prospectively in a separate cohort (n = 132).

MEASUREMENTS AND MAIN RESULTS

The NanoString-based data reproduced two septic shock subclasses. As previously, one subclass had decreased expression of the subclass-defining genes. The gene expression score identified this subclass with an area under the curve of 0.98 (95% confidence interval [CI95] = 0.96-0.99). Prospective testing of the subclassification method corroborated these findings. Allocation to this subclass was independently associated with mortality (odds ratio = 2.7; CI95 = 1.2-6.0; P = 0.016), and adjunctive corticosteroids prescribed at physician discretion were independently associated with mortality in this subclass (odds ratio = 4.1; CI95 = 1.4-12.0; P = 0.011).

CONCLUSIONS

We developed and tested a gene expression-based classification method for pediatric septic shock that meets the time constraints of the critical care environment, and can potentially inform therapeutic decisions.