Identifying Subsets in RCTs and Observational Studies

Transcription

1 Consistent ARDS Endotypes Are Identified Using Minimal Data From A UK/Irish Clinical Trial Identifying Subsets in RCTs and Observational Studies Carolyn S. Calfee, MD MAS Associate Professor of Medicine and Anesthesia University Canadian of California, Critical San Care Francisco Forum American Thoracic November Society International 7 th 2018 Conference May 22, 2017 Pratik Sinha MB ChB PhD FFICM FRCEM Postdoctoral Scholar (Calfee Lab) Division of Pulmonary, Critical Care, UCSF

2 WHY Seek Subsets? ARDS Matthay et al Lanc Resp Med (2017)

3 How About Sepsis? Id

4 Heterogeneity Silver Linings Clinical Biological Temporal We have continued to do Trials We Have A Lot of Data RCTs Observational Studies Genetic HOMOGENEOUS SUBGROUPS / PHENOTYPES

5 Objectives of Seeking Subsets Consistent ARDS Endotypes Are Prognostic Enrichment Identified Using Minimal Data From More likely to encounter outcome of interest A UK/Irish Clinical Trial Carolyn S. Calfee, MD MAS Associate Professor of Medicine and Anesthesia University of California, San Francisco Predictive Enrichment American Thoracic Society International Conference May 22, 2017 More likely to respond to intervention Mehta CR et al Stat Med 2014

6 RCT Pros: Subset Identification: RCT vs Observational Studies Consistent ARDS Endotypes Are Better interpretation of treatment interaction Data is often more complete Cons: Selective Population Secondary Analysis Observational Studies Identified Using Minimal Data From Pros: A UK/Irish Clinical Trial Carolyn S. Calfee, MD MAS Associate Professor of Medicine and Anesthesia University of California, San Francisco Real-world Pragmatic Prospective design Cons: American Thoracic Society International Conference May 22, 2017 Multiple unknown confounders How do we assess effectiveness of identified subgroups?

7 Subgroups in ARDS

8 Latent Class Analysis in RCTs Id Mixture Modelling Unsupervised Clustering Identifies unmeasured subgroups Clinical and Biological Data

9 Standardized Values of Variables in LCA Model Two Phenotypes Identified: Phenotype 2 has Hyper-Inflammatory Characteristics Consistent ARDS Endotypes Are 1 Hypo-inflammatory IL-8, IL-6, stnfr1, PAI-1 Hyper-inflammatory Identified Using Minimal Data From 0.8 Creatinine, Bilirubin A UK/Irish Clinical Trial 30% Hyper- Inflammatory Carolyn S. Calfee, MD MAS Associate Professor of Medicine and Anesthesia University of California, San Francisco American Thoracic Society International Conference Bicarbonate, Protein C, May 22, 2017 Platelets, Systolic BP, Albumin ARMA ALVEOLI FACTT HARP-2 SAILS Sinha et al ICM (2018)

10 Hyper-Inflammatory Phenotype Associated with Worse Outcomes Consistent ARDS Endotypes Are Trial Hypoinflammatory Hyperinflammatory Identified Using Minimal Data From P-value A UK/Irish Clinical Trial ARMA (low TV) 23% 44% ALVEOLI (PEEP) 19% 51% <0.001 Carolyn S. Calfee, MD MAS FACTT (fluids) 22% 45% < Associate Professor of Medicine and Anesthesia University of California, San Francisco HARP2 (simvastatin) 22% 47% < American Thoracic Society International Conference May 22, 2017 SAILS (rosuvastatin) 21% 38% < Calfee Lancet Resp 2014; Famous AJRCCM 2017; Calfee Lancet Resp 2018; Sinha ICM 2018

11 Consistent ARDS Endotypes Are Differential Treatment Response in ARDS Phenotypes Identified Using Minimal Data From Differential Treatment response to: LCA in the HARP-2 Study A UK/Irish Clinical Trial Hypo-inflammatory PEEP (ALVEOLI) Fluid-management strategy (FACTT) Hyper-inflammatory Carolyn S. Calfee, MD MAS Associate Professor of Medicine and Anesthesia University of California, San Francisco American Thoracic Society International Conference May 22, 2017 p = Simvastatin Placebo These effects were not observed when the same populations were stratified by disease severity Calfee et al Lanc Resp Med (2018)

12 Phenotyping in Observational Trials Reactive Bos et al Thorax (2017) Uninflamed

13 Subgroups in Sepsis

14 Is Predictive Enrichment Feasible in Observation studies? Outcome: Complicated Course of Sepsis Glucocorticoid receptor signaling v Id Glucocorticoid receptor signaling v Step 1: Step 2: Prognostic Enrichment Using PERSEVERE (Protein Biomarker) Low risk and Higher Risk Predictive Enrichment Using whole blood RNA to identify Endotypes Endotypes A and B Wong et al CCM (2016)

15 A Cautionary Tale: Biology vs Data Consistent ARDS Endotypes Are Identified Using Minimal Data From A UK/Irish Clinical Trial Carolyn S. Calfee, MD MAS Associate Professor of Medicine and Anesthesia Original Study: Recombinant IL-1RA in Sepsis (JAMA 1994) University of California, San Francisco American Thoracic Society International Conference Heterogeneity of Treatment May 22, Effect: 2017 Subgroups using baseline plasma IL-1RA levels

16 Challenges to Phenotyping

17 Challenges to Phenotyping: Data Sepsis Consistent ARDS Endotypes Are Type Structure Dimensions Identified Using Minimal Data From A UK/Irish Clinical Trial Completeness Noise and outliers Input Data Dictates Identified Clusters Variety Complexity Carolyn S. Calfee, MD MAS Associate Professor of Medicine and Anesthesia University of California, San Francisco American Thoracic Society International Conference May 22, 2017 Sepsis Clusters Input Data

18 Challenges to Phenotyping: Interpretation Secondary analyses Meet criteria for credibility of subgroup analysis* C Ide Generalizability Data-specific Population-specific Mechanistic pathways untested *Sun X et al BMJ (2012)

19 Challenges to Phenotyping: Implementation Model Complexity Models Variables in Model AUC 2-Variable IL-8 + Bicarbonate Variable IL-8 + Bicarbonate + Protein C Variable IL-8 + Bicarbonate + Protein C +Vasopressor Use 0.95 Lack of Point-of-care test for biomarker quantification Time-lag Assay inconsistency Sinha et al ATS 2018

20 Moving Forwards PATIENCE Prospective Evaluation C Ide A priori plan for secondary analysis Robust data collection Diversity of specimens Standard for reporting Are the numerous subgroups described interconnected? Rapid Identification

21 Summary Phenotypes/Endotypes are increasingly being identified in Critical Care Syndromes Route to prognostic and predictive enrichment Currently limited to secondary analysis Rapid identification of phenotypes essential to successful translation

22 Acknowledgements Carolyn Calfee Kevin Delucchi Calfee Lab members Matthay Lab members

23 Questions Useful References: Mrozek S, Jabaudon M, Jaber S, Paugam-Burtz C, Lefrant JY, Rouby JJ, et al. Elevated Plasma Levels of srage Are Associated With Nonfocal CT-Based Lung Imaging in Patients With ARDS: A Prospective Multicenter Study. Chest. 2016;150(5): Calfee CS, Delucchi K, Parsons PE, Thompson BT, Ware LB, Matthay MA, et al. Subphenotypes in acute respiratory distress syndrome: latent class analysis of data from two randomised controlled trials. Lancet Respir Med. 2014;2(8): Calfee CS, Delucchi KL, Sinha P, Matthay MA, Hackett J, Shankar-Hari M, et al. Acute respiratory distress syndrome subphenotypes and differential response to simvastatin: secondary analysis of a randomised controlled trial. Lancet Respir Med. 2018;6(9): Bos LD, Schouten LR, van Vught LA, Wiewel MA, Ong DSY, Cremer O, et al. Identification and validation of distinct biological phenotypes in patients with acute respiratory distress syndrome by cluster analysis. Thorax. 2017;72(10): Meyer NJ, Reilly JP, Anderson BJ, Palakshappa JA, Jones TK, Dunn TG, et al. Mortality Benefit of Recombinant Human Interleukin-1 Receptor Antagonist for Sepsis Varies by Initial Interleukin-1 Receptor Antagonist Plasma Concentration. Crit Care Med. 2018;46(1):21-8. Wong HR, Cvijanovich NZ, Anas N, Allen GL, Thomas NJ, Bigham MT, et al. Developing a clinically feasible personalized medicine approach to pediatric septic shock. Am J Respir Crit Care Med. 2015;191(3): Wong HR, Atkinson SJ, Cvijanovich NZ, Anas N, Allen GL, Thomas NJ, et al. Combining Prognostic and Predictive Enrichment Strategies to Identify Children With Septic Shock Responsive to Corticosteroids. Crit Care Med. 2016;44(10):e1000-3

24 Approach to Identifying Subgroups Primary Dataset: RCT/Observational Study Unsupervised: Discovery Data-driven Clustering (K-mean, hierarchical) Latent Class Analysis Prospective Evaluation Phenotype/Endotype Identification Validation Cohort: Secondary or Prospective Supervised: Regression (standard, Penalized) Recursive Partitioning (CART, Random Forest) Clinically-Viable Classifier Model Confirmatory

25 Defining Subsets In Critical Illness Type Description Discriminating Variables Phenotype Endotype Consistent ARDS Endotypes Are Identified Using Minimal Data From Observable manifestation of genetic response to the environment. A UK/Irish Clinical Trial Carolyn S. Calfee, MD MAS Associate Professor of Medicine and Anesthesia University of California, San Francisco Distinct May 22, 2017 Pathophysiological mechanism / pathway American Thoracic Society International Conference Physiology Laboratory Investigations Biomarkers Genetic Biomarkers Clinical Data Prescott et al AJRCCM 2016

26 Unanswered Questions ARDS Genetic analysis Better understanding of biology of Phenotypes Sepsis Clinical and Biological composite biomarkers Heterogeneous treatment effect in RCTs Both Are the phenotypes and endotypes related Do biological responses differ depending on subphenotypes? Are clinical trials feasible