Predicting Response to Intravesical Therapy in Non–muscle-invasive Bladder Cancer

Mahmoud Alameddine, Omer Kineish, Chad Ritch

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

Context: The ability to predict response to intravesical therapy (IVT) following transurethral resection in non–muscle-invasive bladder cancer holds important prognostic information. However, few predictive tools are available to guide urologists. Objective: We reviewed the most recent studies investigating the predictors of response to IVT. Evidence acquisition: A literature search was conducted using PubMed database from January 1, 2013 to April 1, 2018 following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. For our search strategy, we used the combination of the MeSH terms of “Administration, Intravesical” and “Urinary Bladder Neoplasms” with any of the following words: “Biomarkers,” “Predictive Value of Tests,” “response,” “recurrence,” and “progression.” We limited our search to the English language. Evidence synthesis: Risk stratification models utilizing clinicopathological features are the most cost-effective and widely used tools currently available to predict response to IVT. Additionally, urinary fluorescence in situ hybridization testing and urinary cytokine-based nomograms (Cytokine Panel for Response to Intravesical Therapy) may enhance predictive ability. Protein-based biomarkers have been associated with predicting recurrence. Several gene-based biomarkers quantifying mutations in DNA damage repair genes may have predictive ability. However, genomic data are relatively new and lack validation. Conclusions: Clinicopathological criteria remain the most widely utilized tool for predicting IVT response. Further research to validate protein- and genomic-based biomarkers are needed before adoption in clinical practice. Patient summary: We reviewed contemporary studies that investigated how to predict response to medication instilled in the bladder (intravesical therapy) for bladder cancer. We found that most predictive tools use clinical data, such as tumor stage and grade, to determine the outcome. Newer biological (gene, protein, cytokines) marker tests are being studied. We concluded that the combination of clinical data with levels of certain experimental markers (fluorescence in situ hybridization test or urinary cytokines) may improve predictive ability. Genetic testing methods may also yield additional predictive markers in the future, but this needs more validation. Novel nomograms that combine clinicopathological criteria with the fluorescence in situ hybridization test and/or urinary cytokine expression may constitute a useful approach to predicting intravesical therapy response. Further research into genetic sequencing using large cohorts with follow-up validation is essential to identify novel predictors of response.

Original languageEnglish (US)
JournalEuropean Urology Focus
DOIs
StateAccepted/In press - Jan 1 2018

Fingerprint

Urinary Bladder Neoplasms
Aptitude
Cytokines
Biomarkers
Fluorescence In Situ Hybridization
Nomograms
Therapeutics
Predictive Value of Tests
Intravesical Administration
Recurrence
Genetic Research
Proteins
Genetic Testing
PubMed
DNA Repair
Genes
DNA Damage
Meta-Analysis
Urinary Bladder
Language

Keywords

  • Bacillus Calmette-Guerin
  • Bladder cancer
  • Intravesical therapy
  • Predicting response

ASJC Scopus subject areas

  • Urology

Cite this

Predicting Response to Intravesical Therapy in Non–muscle-invasive Bladder Cancer. / Alameddine, Mahmoud; Kineish, Omer; Ritch, Chad.

In: European Urology Focus, 01.01.2018.

Research output: Contribution to journalArticle

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title = "Predicting Response to Intravesical Therapy in Non–muscle-invasive Bladder Cancer",
abstract = "Context: The ability to predict response to intravesical therapy (IVT) following transurethral resection in non–muscle-invasive bladder cancer holds important prognostic information. However, few predictive tools are available to guide urologists. Objective: We reviewed the most recent studies investigating the predictors of response to IVT. Evidence acquisition: A literature search was conducted using PubMed database from January 1, 2013 to April 1, 2018 following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. For our search strategy, we used the combination of the MeSH terms of “Administration, Intravesical” and “Urinary Bladder Neoplasms” with any of the following words: “Biomarkers,” “Predictive Value of Tests,” “response,” “recurrence,” and “progression.” We limited our search to the English language. Evidence synthesis: Risk stratification models utilizing clinicopathological features are the most cost-effective and widely used tools currently available to predict response to IVT. Additionally, urinary fluorescence in situ hybridization testing and urinary cytokine-based nomograms (Cytokine Panel for Response to Intravesical Therapy) may enhance predictive ability. Protein-based biomarkers have been associated with predicting recurrence. Several gene-based biomarkers quantifying mutations in DNA damage repair genes may have predictive ability. However, genomic data are relatively new and lack validation. Conclusions: Clinicopathological criteria remain the most widely utilized tool for predicting IVT response. Further research to validate protein- and genomic-based biomarkers are needed before adoption in clinical practice. Patient summary: We reviewed contemporary studies that investigated how to predict response to medication instilled in the bladder (intravesical therapy) for bladder cancer. We found that most predictive tools use clinical data, such as tumor stage and grade, to determine the outcome. Newer biological (gene, protein, cytokines) marker tests are being studied. We concluded that the combination of clinical data with levels of certain experimental markers (fluorescence in situ hybridization test or urinary cytokines) may improve predictive ability. Genetic testing methods may also yield additional predictive markers in the future, but this needs more validation. Novel nomograms that combine clinicopathological criteria with the fluorescence in situ hybridization test and/or urinary cytokine expression may constitute a useful approach to predicting intravesical therapy response. Further research into genetic sequencing using large cohorts with follow-up validation is essential to identify novel predictors of response.",
keywords = "Bacillus Calmette-Guerin, Bladder cancer, Intravesical therapy, Predicting response",
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N2 - Context: The ability to predict response to intravesical therapy (IVT) following transurethral resection in non–muscle-invasive bladder cancer holds important prognostic information. However, few predictive tools are available to guide urologists. Objective: We reviewed the most recent studies investigating the predictors of response to IVT. Evidence acquisition: A literature search was conducted using PubMed database from January 1, 2013 to April 1, 2018 following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. For our search strategy, we used the combination of the MeSH terms of “Administration, Intravesical” and “Urinary Bladder Neoplasms” with any of the following words: “Biomarkers,” “Predictive Value of Tests,” “response,” “recurrence,” and “progression.” We limited our search to the English language. Evidence synthesis: Risk stratification models utilizing clinicopathological features are the most cost-effective and widely used tools currently available to predict response to IVT. Additionally, urinary fluorescence in situ hybridization testing and urinary cytokine-based nomograms (Cytokine Panel for Response to Intravesical Therapy) may enhance predictive ability. Protein-based biomarkers have been associated with predicting recurrence. Several gene-based biomarkers quantifying mutations in DNA damage repair genes may have predictive ability. However, genomic data are relatively new and lack validation. Conclusions: Clinicopathological criteria remain the most widely utilized tool for predicting IVT response. Further research to validate protein- and genomic-based biomarkers are needed before adoption in clinical practice. Patient summary: We reviewed contemporary studies that investigated how to predict response to medication instilled in the bladder (intravesical therapy) for bladder cancer. We found that most predictive tools use clinical data, such as tumor stage and grade, to determine the outcome. Newer biological (gene, protein, cytokines) marker tests are being studied. We concluded that the combination of clinical data with levels of certain experimental markers (fluorescence in situ hybridization test or urinary cytokines) may improve predictive ability. Genetic testing methods may also yield additional predictive markers in the future, but this needs more validation. Novel nomograms that combine clinicopathological criteria with the fluorescence in situ hybridization test and/or urinary cytokine expression may constitute a useful approach to predicting intravesical therapy response. Further research into genetic sequencing using large cohorts with follow-up validation is essential to identify novel predictors of response.

AB - Context: The ability to predict response to intravesical therapy (IVT) following transurethral resection in non–muscle-invasive bladder cancer holds important prognostic information. However, few predictive tools are available to guide urologists. Objective: We reviewed the most recent studies investigating the predictors of response to IVT. Evidence acquisition: A literature search was conducted using PubMed database from January 1, 2013 to April 1, 2018 following the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) criteria. For our search strategy, we used the combination of the MeSH terms of “Administration, Intravesical” and “Urinary Bladder Neoplasms” with any of the following words: “Biomarkers,” “Predictive Value of Tests,” “response,” “recurrence,” and “progression.” We limited our search to the English language. Evidence synthesis: Risk stratification models utilizing clinicopathological features are the most cost-effective and widely used tools currently available to predict response to IVT. Additionally, urinary fluorescence in situ hybridization testing and urinary cytokine-based nomograms (Cytokine Panel for Response to Intravesical Therapy) may enhance predictive ability. Protein-based biomarkers have been associated with predicting recurrence. Several gene-based biomarkers quantifying mutations in DNA damage repair genes may have predictive ability. However, genomic data are relatively new and lack validation. Conclusions: Clinicopathological criteria remain the most widely utilized tool for predicting IVT response. Further research to validate protein- and genomic-based biomarkers are needed before adoption in clinical practice. Patient summary: We reviewed contemporary studies that investigated how to predict response to medication instilled in the bladder (intravesical therapy) for bladder cancer. We found that most predictive tools use clinical data, such as tumor stage and grade, to determine the outcome. Newer biological (gene, protein, cytokines) marker tests are being studied. We concluded that the combination of clinical data with levels of certain experimental markers (fluorescence in situ hybridization test or urinary cytokines) may improve predictive ability. Genetic testing methods may also yield additional predictive markers in the future, but this needs more validation. Novel nomograms that combine clinicopathological criteria with the fluorescence in situ hybridization test and/or urinary cytokine expression may constitute a useful approach to predicting intravesical therapy response. Further research into genetic sequencing using large cohorts with follow-up validation is essential to identify novel predictors of response.

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