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Completed

NCT Number: NCT00854607

An Observational Study of Fungal Biomarkers (MK-0000-089)

The purpose of this study is to evaluate the relationship between fungal biomarker levels during anti-fungal therapy and the success of treatment for fungal infection. The primary hypothesis is that over the initial two weeks of anti-fungal therapy, fungal biomarkers from participants with invasive aspergillosis (IA) will be lower for those with a successful clinical outcome compared to those with a failed clinical outcome.

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Key information

Conditions

Aspergillosis Bacterial Infections and Mycoses Infections Mycoses

Age range

16 year and older

Sex eligibility

All sexes

Study type

Observational

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

  • Is 16 years of age or older
  • Female is either post-menopausal, surgically sterilized, willing to use 2 adequate methods of birth control, or agrees to abstain from heterosexual activity throughout the study
  • Female of child bearing potential must have a negative pregnancy test
  • Male is surgically sterilized, agrees to use an adequate method of contraception, or agrees to abstain from heterosexual activity for the duration of the study
  • Has possible, probable, or confirmed invasive aspergillosis (IA)
  • Has had a computed tomography (CT) or magnetic resonance imaging (MRI) scan 72 hours prior to initiation of anti-fungal therapy

Exclusion criteria

  • Has had hemodialysis using cellulose membrane within 2 weeks of study start

Treatment and study plan

No intervention

Other

Blood samples will be collected for 12 weeks to evaluate levels of fungal biomarkers.

Primary outcomes

  1. Average of the Z-scores of the Time-Weighted Averages (TWA) of Fungal Biomarkers Galactomannan (GM) and (1,3)-β-D-glucan (βDG) Over the First Two Weeks of Treatment for Responders (R) and Non-Responders (NonR) to Anti-fungal Treatment at Week 6.

    Time frame: Weeks 1 and 2

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for biomarker analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual TWA divided by the overall standard deviation (SD). The average of the Z-scores of the TWA for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

Secondary outcomes

  1. Average of the Z-scores of the Slopes of Least-Squares Straight Lines (SLSSL) Fitted to the Fungal Biomarkers GM and βDG Over the First Two Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 6.

    Time frame: Weeks 1 and 2

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of biomarkers GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual SLSSL divided by the overall SD. The average Z-scores of the SLSSL for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  2. Average of the Z-scores of the TWA of the Changes From Baseline (CFB) of Fungal Biomarkers GM and βDG Over the First Two Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 6.

    Time frame: Weeks 1 and 2

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual TWA CFB divided by the overall SD. The average of the Z-scores of the TWA CFB for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  3. Average of the Z-scores of the Percent Changes From Baseline (%CFB) of Fungal Biomarkers GM and βDG Over the First Two Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 6.

    Time frame: Weeks 1 and 2

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for biomarker analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual %CFB divided by the overall SD. The average of the Z-scores of the %CFB for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  4. Average of the Z-scores of the SLSSL Fitted to the Fungal Biomarkers GM and βDG Over the First Two Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 12.

    Time frame: Weeks 1 and 2

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for biomarker analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual SLSSL divided by the overall SD. The average Z-scores of the SLSSL for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  5. Average of the Z-scores of the TWA of the CFB of Fungal Biomarkers GM and βDG Over the First Two Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 12.

    Time frame: Weeks 1 and 2

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual TWA CFB divided by the overall SD. The average of the Z-scores of the TWA CFB for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  6. Average of the Z-scores of %CFB of Fungal Biomarkers GM and βDG Over the First Two Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 12.

    Time frame: Weeks 1 and 2

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for biomarker analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual %CFB divided by the overall SD. The average of the Z-scores of the %CFB for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  7. Average of the Z-scores of the TWA of Fungal Biomarkers GM and βDG Over the First Week of Treatment for R and NonR to Anti-fungal Treatment at Week 6.

    Time frame: Week 1

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual TWA divided by the overall SD. The average of the Z-scores of the TWA for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  8. Average of the Z-scores of the TWA of Fungal Biomarkers GM and βDG Over the First Week of Treatment for R and NonR to Anti-fungal Treatment at Week 12.

    Time frame: Week 1

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual TWA divided by the overall SD. The average of the Z-scores of the TWA for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  9. Average of the Z-scores of the SLSSL Fitted to the Fungal Biomarkers GM and βDG Over the First Week of Treatment for R and NonR to Anti-fungal Treatment at Week 6.

    Time frame: Week 1

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of biomarkers GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual SLSSL divided by the overall SD. The average Z-scores of the SLSSL for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  10. Average of the Z-scores of the SLSSL Fitted to the Fungal Biomarkers GM and βDG Over the First Week of Treatment for R and NonR to Anti-fungal Treatment at Week 12.

    Time frame: Week 1

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of biomarkers GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual SLSSL divided by the overall SD. The average Z-scores of the SLSSL for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  11. Average of the Z-scores of the TWA of Fungal Biomarkers GM and βDG Over the First 6 Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 6.

    Time frame: Weeks 1 through 6

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual TWA divided by the overall SD. The average of the Z-scores of the TWA for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  12. Average of the Z-scores of the TWA of Fungal Biomarkers GM and βDG Over the First 6 Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 12.

    Time frame: Weeks 1 through 6

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual TWA divided by the overall SD. The average of the Z-scores of the TWA for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  13. Average of the Z-scores of the SLSSL Fitted to the Fungal Biomarkers GM and βDG Over the First 6 Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 6.

    Time frame: Weeks 1 through 6

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of biomarkers GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual SLSSL divided by the overall SD. The average Z-scores of the SLSSL for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

  14. Average of the Z-scores of the SLSSL Fitted to the Fungal Biomarkers GM and βDG Over the First 6 Weeks of Treatment for R and NonR to Anti-fungal Treatment at Week 12.

    Time frame: Weeks 1 through 6

    After enrollment blood was collected at baseline, twice per week for the first six weeks, then weekly through twelve weeks for analysis of biomarkers GM and βDG. Clinical outcome was assessed for qualified participants at 6 and 12 weeks after initiation of antifungal treatment. For a given biomarker the Z-score is the difference from the mean of each individual SLSSL divided by the overall SD. The average Z-scores of the SLSSL for qualified participants is then calculated across all biomarkers, and used to derive the mean for R and NonR to antifungal therapy.

Sponsors and collaborators

Lead sponsor

Merck Sharp & Dohme LLC

Industry

Registry information

Official study title

A Prospective, Non-Intervention, Observational Assessment of the Correlation Between Circulating Biomarkers of Fungal Bioburden and Clinical Outcome in the Setting of Invasive Aspergillosis

Important dates

Study start
2009
Primary completion
2011
Study completion
2011
First posted
Mar 3, 2009
Registry last updated
Aug 21, 2015

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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