Trend Watch

Epidemiology Model Addresses Needs of Long-Term HCV Patients

Decision Resources Group has introduced a novel epidemiology model to help pharmaceutical companies predict long-term hepatitis C virus patient populations by country and treatment scenario, according to a press release.

The product, known as the HCV Interactive Patient Flow Model, produces individual 15-year forecasts of the HCV patient population for 45 countries based on five different treatment scenarios for those markets, according to the release. Because the HCV global market’s unique complexities make accurately predicting the landscape a challenge, the model uses interactive patient flow diagrams and extensive data sets to show size and flow of more than 50 patient populations across four HCV disease genotypes, per the release.

Although direct-acting antiviral therapies present an effective cure for HCV, the treatment is costly and cannot be distributed to everyone, suggesting that access to DAAs varies from country to country, according to the release. Therefore, HCV Interactive Patient Flow Model, which can examine how different treatment scenarios will impact the potential value of these markers, is vital, per the release. The model takes into consideration five different versions of the 15-year forecast for each country, including:

the most likely outcome within each market;

  • without DAAs;
  • with resource restrictions;
  • without resource restrictions; and
  • will meet WHO’s goals for diagnosis and treatment by 2030.

“The HCV patient landscape is changing quickly and there is considerable risk in getting it wrong, so it’s important to understand some of these varying scenarios,” Seth Kuranz, MPH, epidemiologist at Decision Resources Group, said in the release. “Through this product, we are helping companies understand and communicate to their stakeholders how certain treatment assumptions might impact the size of the HCV population and the progression of the epidemic in any given country.”

Disclosures: Kuranz is an employee of Decision Resources Group.

Decision Resources Group has introduced a novel epidemiology model to help pharmaceutical companies predict long-term hepatitis C virus patient populations by country and treatment scenario, according to a press release.

The product, known as the HCV Interactive Patient Flow Model, produces individual 15-year forecasts of the HCV patient population for 45 countries based on five different treatment scenarios for those markets, according to the release. Because the HCV global market’s unique complexities make accurately predicting the landscape a challenge, the model uses interactive patient flow diagrams and extensive data sets to show size and flow of more than 50 patient populations across four HCV disease genotypes, per the release.

Although direct-acting antiviral therapies present an effective cure for HCV, the treatment is costly and cannot be distributed to everyone, suggesting that access to DAAs varies from country to country, according to the release. Therefore, HCV Interactive Patient Flow Model, which can examine how different treatment scenarios will impact the potential value of these markers, is vital, per the release. The model takes into consideration five different versions of the 15-year forecast for each country, including:

the most likely outcome within each market;

  • without DAAs;
  • with resource restrictions;
  • without resource restrictions; and
  • will meet WHO’s goals for diagnosis and treatment by 2030.

“The HCV patient landscape is changing quickly and there is considerable risk in getting it wrong, so it’s important to understand some of these varying scenarios,” Seth Kuranz, MPH, epidemiologist at Decision Resources Group, said in the release. “Through this product, we are helping companies understand and communicate to their stakeholders how certain treatment assumptions might impact the size of the HCV population and the progression of the epidemic in any given country.”

Disclosures: Kuranz is an employee of Decision Resources Group.