Observational Study of Sepsis and Pneumonia to Develop Diagnostic Tests

The recruitment status of this study is unknown. The completion date has passed and the status has not been verified in more than two years.
Verified January 2009 by National Center for Genome Resources.
Recruitment status was:  Recruiting
Sponsor:
Collaborators:
National Institute of Allergy and Infectious Diseases (NIAID)
Duke University
Henry Ford Hospital
Durham VA Medical Center
Pfizer
Hoffmann-La Roche
Information provided by:
National Center for Genome Resources
ClinicalTrials.gov Identifier:
NCT00258869
First received: November 23, 2005
Last updated: November 5, 2010
Last verified: January 2009
  Purpose

We propose to develop novel diagnostic tests for severe sepsis and community acquired pneumonia (CAP). This program, entitled Community Acquired Pneumonia & Sepsis Outcome Diagnostics (CAPSOD), is a multidisciplinary collaboration involving investigators at six organizations: NCGR; Duke University Medical Center, Durham, NC; Henry Ford Hospital, Detroit, MI; Eli Lilly and Company, Indianapolis, IN; Indiana Centers for Applied Protein Sciences, Indianapolis, IN; and ProSanos Corp., La Jolla, CA.

In the United States, Community Acquired Pneumonia is the sixth leading cause of death and the number one cause of death from infectious diseases. Of the 5.6 million annual cases of CAP, 1.1 million require hospitalization for intensive therapy. Sepsis, commonly known as blood poisoning or bloodstream infection, is the tenth leading cause of death in the US and the number one cause of death in non-cardiac intensive care units. Incidence of sepsis is increasing by 9% each year and mortality rates vary between 25 and 50%. Cost to the US healthcare system exceeds $20 billion each year.

In patients with suspected sepsis or early CAP, rapid identification of patients who will develop severe sepsis or CAP is critical for effective management and positive outcome. The CAPSOD study is designed to identify novel tests for early diagnosis of severe sepsis and CAP. When performed in patients at the earliest stages of disease, these tests will have prognostic value, rapidly identifying those who will have poor outcomes or complicated courses.

CAPSOD will prospectively enroll patients with sepsis and CAP at Duke University Medical Center and Henry Ford Hospital. The study will use advanced bioinformatic, metabolomic, proteomic and mRNA sequencing technologies to identify specific protein changes, or biomarkers, in patient blood samples that predict outcome in sepsis and CAP. Development of biomarker-based tests will permit patient selection for appropriate disposition, such as the intensive care unit, and use of intensive medical therapies, thereby reducing mortality and increasing effectiveness of resource allocation.


Condition
Sepsis
Septicemia
Sepsis Syndrome
Shock, Septic
Community Acquired Pneumonia

Study Type: Observational
Study Design: Observational Model: Cohort
Time Perspective: Prospective
Official Title: Plasma Protein Biomarker Based Diagnostics of Outcome in Sepsis & CAP

Resource links provided by NLM:


Further study details as provided by National Center for Genome Resources:

Primary Outcome Measures:
  • Death [ Time Frame: Day 3 ]
  • Septic Shock [ Time Frame: Day 3 ]
  • Severe Sepsis [ Time Frame: Day 3 ]

Secondary Outcome Measures:
  • Time to death [ Time Frame: 28 days ]
  • Death [ Time Frame: Day 5 ]
  • Death [ Time Frame: Day 7 ]
  • Death [ Time Frame: Day 28 ]
  • Time to severe sepsis [ Time Frame: 28 days ]
  • Severe sepsis [ Time Frame: Day 5 ]
  • Severe sepsis [ Time Frame: Day 7 ]
  • Severe sepsis [ Time Frame: Day 28 ]
  • Time to septic shock [ Time Frame: 28 days ]
  • Septic Shock [ Time Frame: Day 5 ]
  • Septic Shock [ Time Frame: Day 7 ]
  • Septic shock [ Time Frame: Day 28 ]
  • Cryptic shock (ScvO2<65 or Lactate >2.5 and MAP >65 mmHg [>18 years of age] or SBP >90 [<18 years of age]) [ Time Frame: Day 3 ]
  • Time to Cryptic shock (ScvO2<65 or Lactate >2.5 and MAP >65 mmHg [>18 years of age] or SBP >90 [<18 years of age]) [ Time Frame: Day 28 ]
  • Cryptic shock (ScvO2<65 or Lactate >2.5 and MAP >65 mmHg [>18 years of age] or SBP >90 [<18 years of age]) [ Time Frame: Day 5 ]
  • Cryptic shock (ScvO2<65 or Lactate >2.5 and MAP >65 mmHg [>18 years of age] or SBP >90 [<18 years of age]) [ Time Frame: Day 7 ]
  • Cryptic shock (ScvO2<65 or Lactate >2.5 and MAP >65 mmHg [>18 years of age] or SBP >90 [<18 years of age]) [ Time Frame: Day 28 ]
  • Hospitalization [ Time Frame: 24 hours ]
  • Length of hospital stay [ Time Frame: Days ]
  • ICU admission [ Time Frame: 28 days ]
  • Length of ICU admission [ Time Frame: Days ]
  • Disposition [ Time Frame: 28 day ]
  • Renal dysfunction [ Time Frame: 28 days ]
  • Respiratory dysfunction [ Time Frame: 28 days ]
  • Hematology dysfunction [ Time Frame: 28 days ]
  • Metabolic dysfunction [ Time Frame: 28 days ]
  • Renal SOFA score [ Time Frame: 28 days ]
  • Lung SOFA score [ Time Frame: 28 days ]
  • Coagulation SOFA score [ Time Frame: 28 days ]
  • Liver SOFA score [ Time Frame: 28 days ]
  • CVS SOFA score [ Time Frame: 28 dadys ]
  • Time to respiratory SOFA Score [ Time Frame: 28 days ]
  • Time to coagulation SOFA score [ Time Frame: 28 days ]
  • Time to liver SOFA score [ Time Frame: 28 days ]
  • Time to CVS SOFA score [ Time Frame: 28 days ]
  • Time to Renal SOFA score [ Time Frame: 28 days ]
  • DIC score >5 (modified ISTH scoring system) [ Time Frame: 28 days ]
  • Time to DIC score > 5 [ Time Frame: Days ]
  • Development of ALI [ Time Frame: 28 days ]
  • Development of ARDS [ Time Frame: 28 days ]
  • Time to ALI [ Time Frame: Days ]
  • Time to ARDS [ Time Frame: Days ]
  • Ventilator [ Time Frame: 28 days ]
  • Ventilator days [ Time Frame: Days ]
  • MELD score [ Time Frame: 28 days ]
  • Effect of early goal directed therapy on primary and secondary end-points [ Time Frame: 28 days ]
  • Effect of Activated Protein C on primary and secondary end-points [ Time Frame: 28 days ]
  • Effect of stress-dose corticosteroids on primary and secondary end-points [ Time Frame: 28 days ]
  • Effect of intensive glycemic control on primary and secondary end-points [ Time Frame: 28 days ]
  • APACHE II score [ Time Frame: enrollment ]
  • APACHE II score [ Time Frame: 24 hours ]
  • PRISM III score [ Time Frame: enrollment ]
  • PRISM III score [ Time Frame: 24 hours ]
  • SOFA score [ Time Frame: enrollment ]
  • SOFA score [ Time Frame: 24 hours ]
  • CAP mortality [ Time Frame: Day 3 ]
  • CAP and severe sepsis [ Time Frame: Day 3 ]
  • CAP and septic shock [ Time Frame: Day 3 ]
  • Severe CAP (ATS criteria) [ Time Frame: Day 3 ]
  • Severe CAP (BTS criteria) [ Time Frame: Day 3 ]
  • Pneumococcal sepsis [ Time Frame: Day 7 ]
  • Staphylococcus aureus sepsis [ Time Frame: Day 7 ]
  • Gram negative rod sepsis [ Time Frame: Day 7 ]
  • Fungal sepsis [ Time Frame: Day 7 ]
  • SeptiFast result [ Time Frame: Enrollment ]
  • SeptiFast result [ Time Frame: 24 hours ]
  • Microbiologic culture result [ Time Frame: Day 28 ]
  • Urinary legionella antigen [ Time Frame: 7 days ]
  • Microbiologic culture [ Time Frame: 7 days ]
  • CAP, time to death [ Time Frame: days ]
  • CAP, mortality [ Time Frame: Day 5 ]
  • CAP, mortality [ Time Frame: Day 7 ]
  • CAP, mortality [ Time Frame: Day 28 ]
  • CAP, time to severe sepsis [ Time Frame: Days ]
  • CAP, severe sepsis [ Time Frame: Day 5 ]
  • CAP, severe sepsis [ Time Frame: Day 7 ]
  • CAP, severe sepsis [ Time Frame: Day 28 ]
  • CAP, time to septic shock [ Time Frame: days ]
  • CAP, septic shock [ Time Frame: Day 5 ]
  • CAP, septic shock [ Time Frame: Day 7 ]
  • CAP, septic shock [ Time Frame: Day 28 ]
  • Time to severe CAP (ATS and BTS criteria) [ Time Frame: Days ]
  • Severe CAP (ATS and BTS criteria) [ Time Frame: Day 5 ]
  • Severe CAP (ATS and BTS criteria) [ Time Frame: Day 7 ]
  • Severe CAP (ATS and BTS criteria) [ Time Frame: Day 28 ]
  • CAP, mechanical ventilation [ Time Frame: 28 days ]
  • CAP, time to mechanical ventilation [ Time Frame: Days ]
  • CAP, length of mechanical ventilation [ Time Frame: Days ]
  • CAP, SOFA respiratory score > 2 [ Time Frame: 28 days ]
  • CAP, respiratory component of severe sepsis criteria [ Time Frame: 28 days ]
  • CAP, hospitalized [ Time Frame: 24 hours ]
  • CAP, length of hospitalization [ Time Frame: Days ]
  • CAP, ICU admission [ Time Frame: 28 days ]
  • CAP, length of ICU stay [ Time Frame: Days ]
  • CAP, Disposition [ Time Frame: 28 days ]
  • CAP, ALI [ Time Frame: 28 days ]
  • CAP, ARDS [ Time Frame: 28 days ]
  • CAP, time to ARDS [ Time Frame: days ]
  • CAP, time to ALI [ Time Frame: Days ]
  • CAP, PORT score [ Time Frame: enrollment ]
  • CAP, PORT score [ Time Frame: 24 hours ]

Biospecimen Retention:   Samples With DNA
PaxGene whole blood tubes (RNA and DNA), EDTA plasma, serum (subset), microbiologic isolates

Estimated Enrollment: 1200
Study Start Date: December 2005
Estimated Study Completion Date: July 2010
Estimated Primary Completion Date: July 2010 (Final data collection date for primary outcome measure)
Groups/Cohorts
1
Emergency department patients with sepsis

  Hide Detailed Description

Detailed Description:

3 interdependent aims are proposed to discover and initiate development of novel, in vitro diagnostic tests (IVD) for severe sepsis (SS) and community acquired pneumonia (CAP).

Specific Aim 1: Discovery and initial development of an IVD for early diagnosis of severe sepsis.

In patients with suspected sepsis, early, accurate identification of patients who will develop organ dysfunction (SS) is critical for effective management and positive outcome. While the American College of Chest Physicians/Society of Critical Care Medicine Consensus Conference definitions provide a clinical guide to identifying patients who have SS, we propose to develop a rapid, point-of-care (POC) IVD for early diagnosis of SS. The basis of the proposed IVD will be the measurement of several, host response, plasma proteins. When performed in patients at the earliest stage of sepsis, this test will have prognostic value, rapidly identifying patients who will have poor outcomes or complicated courses.

Availability of this IVD will enable patient selection for appropriate disposition, such as the intensive care unit (ICU), and use of medical therapies, such as early goal-directed therapy (EGDT), thereby reducing mortality and increasing effectiveness of resource allocation. A considerable literature exists of host plasma protein changes during sepsis. Furthermore, in preliminary studies measuring more than 100 host proteins in blood of over 300 patients with SS, we have identified a number of candidate biomarkers of SS. We propose to inventory, replicate and validate the utility of these biomarkers of SS, and to identify novel plasma biomarkers of SS, through literature review and a prospective clinical study employing 2 proteomic technologies (mass spectrometry and multiplexed immunoassays), mass spectrometry-based plasma metabolomics and sequencing of mRNA derived from peripheral blood lymphocytes. We intend to enroll 1200 patients with sepsis (evidence of infection and 2 or more criteria of the systemic inflammatory response syndrome, SIRS) at 3 US tertiary care hospitals and emergency departments (ED), and to monitor their course both by established clinical severity indices (Acute Physiology and Chronic Health Evaluation [APACHE II] and Pneumonia Patient Outcomes Research Team [PORT]scores, and metabolic endpoints such as lactate, base deficit and pH) and ascertainment of complicating events (such as SS, septic shock, acute renal failure (ARF), acute respiratory distress syndrome (ARDS),disseminated intravascular coagulopathy (DIC) and death). It is anticipated that approximately 60% of the patients will develop SS.

Data will be stored in an anonymized, encrypted, web-based patient registry. Bivariable analyses will be performed to identify and validate biomarker differences between groups. Furthermore, we intend to perform predictive modeling using multivariable analyses of the validated biomarkers and derive a biomarker panel and algorithm for early diagnosis of SS. The predictive value of the biomarker panel for early diagnosis of SS will be compared with established prognostic indices, such as metabolic endpoints and APACHE II score. Novel biomarkers of severe CAP will be identified by mass spectrometry of patient EDTA plasma samples. Subject to availability of multiplexed immunoassays, some of these biomarkers will be replicated by immunoassay in the same samples.

During the period of award, a plan for IVD development of the biomarker panel for early diagnosis of SS will be developed. This is anticipated to involve assay optimization and transfer to an existing, validated IVD platform, FDA-regulated IVD development processes, and incorporation of the IVD into an intensive treatment algorithm. The proposed IVD will be an oligoplex assay performed on a single blood sample using immunoassays on an established diagnostic platform with time-to-first result of less than 30 minutes and capable of use in a POC setting, such as an ED or ICU.

Specific Aim 2: Biomarker development for early differentiation of poor outcome in CAP Complications of CAP, including respiratory failure, other organ system failure and severe sepsis, are major determinants of morbidity and mortality. At time of presentation with CAP, accurate identification of patients who will have a complicated course or poor outcome is critical for effective management and positive outcome. In parallel with Specific Aim 1, we propose to identify biomarkers for early diagnosis/prognosis of poor outcome in patients with CAP ("severe CAP"). The biomarkers will be several, host response, plasma proteins that differentiate mild and severe CAP. Early diagnosis of severe CAP will enable patient selection for hospitalization, thereby reducing mortality and increasing effectiveness of resource allocation.

It is anticipated that approximately 33% of the patients enrolled in the Specific Aim 1 clinical study (evidence of infection and two or more SIRS criteria) will have CAP as the underlying infection causing sepsis. Furthermore, it is anticipated that approximately 25% of these CAP patients will develop severe CAP. Specific aim 2 proposes a secondary, separate analysis of all patients enrolled in the Specific Aim 1 clinical study who have CAP in order to identify biomarkers for early diagnosis of severe CAP. We propose to inventory existing candidate biomarkers of severe CAP through literature review. Furthermore, we propose to validate the utility of some of these biomarkers, and to identify a number of novel biomarkers of severe CAP through analysis of the subset of patients in the prospective clinical study who have CAP and employing 2 proteomic technologies (mass spectrometry and multiplexed immunoassays), mass spectrometry-based plasma metabolomics and sequencing of mRNA derived from peripheral blood lymphocytes. Bivariable analyses will be performed to identify plasma biomarker differences between mild and severe CAP. Multivariable analyses will be performed in order to derive a plasma biomarker panel and algorithm for early diagnosis of severe CAP. The biomarker panel for early diagnosis of severe CAP will be compared with established prognostic indices, such as PORT score. Novel biomarkers of severe CAP will be identified by mass spectrometry of patient EDTA plasma samples.

Subject to availability of multiplexed immunoassays, some of these biomarkers will be replicated by immunoassay in the same samples.

During the period of award, a plan for panel validation and IVD development for early diagnosis of severe CAP will be developed. The latter is anticipated to involve assay optimization and transfer to an existing, validated IVD platform, FDA regulated IVD development processes, and incorporation of the IVD into an intensive treatment algorithm. The proposed IVD will be an oligoplex assay performed on a single blood sample using immunoassays on an established diagnostic platform with time-to-first result of less than 30 minutes and capable of use in a POC setting, such as an ED or ICU. This is anticipated to be a product line extension of the SS IVD.

Specific Aim 3: Biomarker development for early differentiation of sepsis and CAP pathogens Currently, initial antimicrobial treatment of sepsis and CAP is empiric. Common etiologic agents in sepsis are gram-positive bacteria (Staphylococcus spp. and Streptococcus spp.), gram-negative bacteria (e.g., Escherichia coli, Klebsiella spp., and Enterobacter spp.), and fungi (Candida spp.). Common etiologic agents in CAP are Streptococcus pneumoniae, Legionella pneumophila, Mycoplasma spp., and viruses. The ability to distinguish these pathogens at time of presentation of sepsis or CAP would potentially allow more targeted rather than broad-spectrum initial therapy. Earlier administration of appropriate antimicrobials would lower patient management cost associated with ineffective therapy and lessen likelihood of antibiotic resistance. We propose to identify host biomarkers for early differentiation of up to 4 common etiologic agents in sepsis and CAP. Our preliminary studies have established proof-of-concept for differentiation between classes of pathogens in sepsis based on specific differences in soluble host proteins in a blood sample. Based on our preliminary studies, it is anticipated that approximately 25% of patients in the Specific Aim 1 clinical study will have a positive blood culture. At least 33 of these patients are anticipated to have S. aureus bacteremia and 20 gram negative bacteremia. Specific Aim 3 proposes to compare plasma samples from patients with S. aureus and gram negative bacteremia in order to identify host biomarkers for early differentiation of specific class agent in sepsis. As in specific aims 1 and 2, bivariable and multivariable analyses of biomarkers is proposed to develop a biomarker panel for early differentiation of staphylococcal and gram-negative sepsis. Similar analysis is proposed to differentiate CAP pathogens. However, given the absence of a high-sensitivity, gold-standard method for determination of causal pathogen in CAP, Specific Aim 3 proposes the more conservative goal of differentiating pneumococcal CAP from atypical CAP based on quantitative differences in host blood biomarkers. The pneumococcal CAP group will be selected from the clinical studydataset based on rigorous criteria: S. pneumoniae from blood or sputum culture or detection of pneumococcal antigen in urine, clinical evidence of CAP and typical (lobar consolidation) chest radiograph. The nonpneumococcal CAP group will be determined by negative pneumococcal cultures and urine antigen, clinical evidence of CAP, and an atypical chest radiograph. It is anticipated that at least 20 patients (15% of the 133 with CAP) will have confirmed pneumococcal CAP and 40 patients (30%) atypical, non-pneumococcal CAP. Biomarkers for differentiation of i. S. aureus bacteremia from gram-negative bacteremia, and ii. pneumococcal CAP from atypical CAP, will be identified by mass spectrometry of patient EDTA plasma samples. Subject to availability of multiplexed immunoassays, some of these biomarkers will be replicated by immunoassay in the same samples. It should be noted that given budget-imposed reduction in patient enrollment of one third from that originally proposed, we are uncertain that sufficient patients will be enrolled for all Specific Aim 3 analyses to be meaningful. We propose to evaluate the group sizes of enrolled patients by specific class agent in order to select two specific comparisons between sepsis and CAP pathogens that are of sufficient size to permit meaningful analysis.

Validation and development of these biomarkers into biomarker panels and rapid, POC, IVD for early differentiation of pathogen in sepsis and CAP is intended, but is beyond the scope of the present proposal. A product line extension of the SS IVD is envisaged. Like the test for early diagnosis of SS, the IVD(s) for early differentiation of CAP and sepsis pathogens will be oligoplex assay(s) performed on single blood sample(s) using immunoassays or other analyte assays.

  Eligibility

Ages Eligible for Study:   6 Years and older   (Child, Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No
Sampling Method:   Non-Probability Sample
Study Population
Emergency department patients > 6 years of age
Criteria

Inclusion Criteria:

1. Patient has known or acute infection or suspected infection AND patient must meet at least 2 of the following 4 criteria to be enrolled

  1. A core temperature of >= 38°C (100.4°F) or <= 36°C (96.8°F)
  2. Patients > 18 years of age, Heart rate of >= 90 beats/min Patients 13-18 years of age, Heart rate of >= 110 beats/min Patients 6-12 years of age, Heart rate of >= 130 beats/min
  3. Patients > 18 years of age, Respiratory rate of >= 20 breaths/min Patients 13-18 years of age, Respiratory rate of >= 14 breaths/min Patients 6-12 years of age, Respiratory rate of >= 18 breaths/min OR PaCO2 of <= 32 mm Hg OR Use of Mechanical Ventilation for an acute respiratory process
  4. Patients > 18 years of age, White cell count >= 12,000/mm3 or <= 4,000/mm3 Patients 13-18 years of age, White cell count >= 11,000/mm3 or <= 4,500/mm3 Patients 6-12 years of age, White cell count >= 13,500/mm3 or <= 4,500/mm3 OR A differential count showing > 10% immature neutrophils

Exclusion Criteria:

  1. Patient is less than 6 years of age.
  2. Patient is not expected to survive 28 days because of uncorrectable medical condition (apart from pneumonia or sepsis), such as poorly controlled neoplasm or other end-stage disease, or patient has active DNR order
  3. Human immunodeficiency virus (HIV) infection with a last known CD4 count of <50 mm3
  4. Acute presence of a cerebral vascular event, active gastrointestinal hemorrhage, seizure (acute episode), drug overdose, burn injury, trauma
  5. Patient is pregnant
  Contacts and Locations
Choosing to participate in a study is an important personal decision. Talk with your doctor and family members or friends about deciding to join a study. To learn more about this study, you or your doctor may contact the study research staff using the Contacts provided below. For general information, see Learn About Clinical Studies.

Please refer to this study by its ClinicalTrials.gov identifier: NCT00258869

Locations
United States, Michigan
Henry Ford Hospital
Detroit, Michigan, United States, 48202
United States, North Carolina
Duke University Medical Center
Durham, North Carolina, United States, 27710
Durham VA Medical Center
Durham, North Carolina, United States, 27710
Sponsors and Collaborators
National Center for Genome Resources
National Institute of Allergy and Infectious Diseases (NIAID)
Duke University
Henry Ford Hospital
Durham VA Medical Center
Pfizer
Hoffmann-La Roche
Investigators
Principal Investigator: Stephen F Kingsmore, MB ChB BAO National Center for Genome Resources
Study Director: Vance Jr G Fowler, MD Duke University
Study Director: Emanuel P Rivers, MD Henry Ford Hospital
Study Director: Christopher W Woods, MD Duke University
Study Director: Ralph G Corey, MD Duke University
Study Director: Ronny Otero, MD Henry Ford Hospital
Study Director: Brian W Grinnell, PhD Eli Lilly and Company
Study Director: Brian T Edmonds, PhD Eli Lilly and Company
Study Director: Mu Wang, PhD INCAPS
Study Director: James R Ludwig, PhD INCAPS
  More Information

Additional Information:
Publications:

Publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):
Responsible Party: Stephen F. Kingsmore, President, National Center for Genome Resources
ClinicalTrials.gov Identifier: NCT00258869     History of Changes
Other Study ID Numbers: 0001  U01AI066569 
Study First Received: November 23, 2005
Last Updated: November 5, 2010

Keywords provided by National Center for Genome Resources:
prospective studies
biological assay
body weights and measures
chemistry, analytical
microchip analytical procedures
spectrum analysis, mass
molecular diagnostic techniques
microbiological techniques
drug administration schedule
data collection
statistics
gene expression profiling
sequence analysis
human experimentation
immunoassay
Trauma severity indices
Glasgow Coma score
Outcome assessment
mortality
computer models
decision modeling
linear models
logistic models
immunologic model
mathematical model
non-linear models
early diagnosis
diagnosis, computer assisted
medical informatics
prognosis

Additional relevant MeSH terms:
Sepsis
Toxemia
Pneumonia
Systemic Inflammatory Response Syndrome
Shock, Septic
Infection
Inflammation
Pathologic Processes
Lung Diseases
Respiratory Tract Diseases
Respiratory Tract Infections
Shock

ClinicalTrials.gov processed this record on January 19, 2017