Title: Cost-effectiveness of NALIRIFOX versus Nab-paclitaxel and Gemcitabine in Previously
Untreated Metastatic Pancreatic Ductal Adenocarcinoma
Version: 2 Date: 17 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The model assumes that patients who do not receive second-line therapy in either group receive
the best supportive care (BSC), which may not fully reflect the complexity of treatment decisions
or the potential for off-label or clinical trial participation. Additionally, the assumption of no
cost adjustment for half of the cycle in the first model cycle could be an oversimplification that
may affect the precision of cost estimates, especially in treatments with staggered administration
schedules.
-The analysis focuses solely on direct medical costs, excluding potential indirect costs such as
lost productivity or caregiver costs, which can be significant in cancer treatment. The inclusion
of indirect costs could provide a more comprehensive economic evaluation.
-The utility values used for progression-free survival (PFS), progression of disease (PD), and
mortality states (0.81, 0.73, and 0) are sourced from existing literature. However, these values
might not fully reflect patient experiences or preferences in the U.S., which could limit the
generalizability of the results. Additionally, disutility values related to adverse events (AEs) are
based on prior studies but could vary across populations or healthcare settings.
-The model extrapolates survival data from the NAPOLI 3 trial using Weibull and Gamma
distributions, but this can introduce some uncertainty, especially in extrapolating long-term
survival outcomes. The models assume similar rates of AE incidence in both treatment arms,
but there may be subtle differences in how AEs impact patients in real-world settings.
-Although the model uses data from the NAPOLI 3 trial and other relevant sources, it would
benefit from external validation using other cohorts or real-world data. This could help verify
the generalizability of the findings across different patient populations or healthcare settings.
-The model assumes a fixed cost and utility loss from grade #3 adverse events with an incidence
of #5%, but in practice, the severity and impact of these events can vary widely between
individuals. Including a more granular assessment of AE heterogeneity could improve the
model’s precision.
-While the study extrapolates long-term survival from Kaplan-Meier curves, it relies on trial data
that may not fully capture real-world treatment outcomes. Given that clinical trial participants
often do not represent the full spectrum of patients in the real world, additional data from
observational studies or real-world evidence would strengthen the study's findings.
-The assumption that treatment costs remain constant over time (without considering potential
price reductions or generics) might lead to an overestimation of long-term costs. Future studies
could benefit from incorporating dynamic pricing models that account for drug price reductions
over time, especially as new generics or alternative therapies enter the market.
-The study uses conventional WTP thresholds ($50,000, $100,000, $150,000) to assess cost-
effectiveness. However, these thresholds may not fully capture the value of therapies for terminal
diseases like mPDAC, where treatment offers limited survival benefits but might significantly
improve patient's quality of life in the short term. Moreover, there is no universally accepted
WTP threshold in the US, making these values somewhat arbitrary.
Title: Cost-effectiveness of NALIRIFOX versus Nab-paclitaxel and Gemcitabine in Previously
Untreated Metastatic Pancreatic Ductal Adenocarcinoma
Version: 2 Date: 17 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The model assumes that patients who do not receive second-line therapy in either group receive
the best supportive care (BSC), which may not fully reflect the complexity of treatment decisions
or the potential for off-label or clinical trial participation. Additionally, the assumption of no
cost adjustment for half of the cycle in the first model cycle could be an oversimplification that
may affect the precision of cost estimates, especially in treatments with staggered administration
schedules.
-The analysis focuses solely on direct medical costs, excluding potential indirect costs such as
lost productivity or caregiver costs, which can be significant in cancer treatment. The inclusion
of indirect costs could provide a more comprehensive economic evaluation.
-The utility values used for progression-free survival (PFS), progression of disease (PD), and
mortality states (0.81, 0.73, and 0) are sourced from existing literature. However, these values
might not fully reflect patient experiences or preferences in the U.S., which could limit the
generalizability of the results. Additionally, disutility values related to adverse events (AEs) are
based on prior studies but could vary across populations or healthcare settings.
-The model extrapolates survival data from the NAPOLI 3 trial using Weibull and Gamma
distributions, but this can introduce some uncertainty, especially in extrapolating long-term
survival outcomes. The models assume similar rates of AE incidence in both treatment arms,
but there may be subtle differences in how AEs impact patients in real-world settings.
-Although the model uses data from the NAPOLI 3 trial and other relevant sources, it would
benefit from external validation using other cohorts or real-world data. This could help verify
the generalizability of the findings across different patient populations or healthcare settings.
-The model assumes a fixed cost and utility loss from grade #3 adverse events with an incidence
of #5%, but in practice, the severity and impact of these events can vary widely between
individuals. Including a more granular assessment of AE heterogeneity could improve the
model’s precision.
-While the study extrapolates long-term survival from Kaplan-Meier curves, it relies on trial data
that may not fully capture real-world treatment outcomes. Given that clinical trial participants
often do not represent the full spectrum of patients in the real world, additional data from
observational studies or real-world evidence would strengthen the study's findings.
-The assumption that treatment costs remain constant over time (without considering potential
price reductions or generics) might lead to an overestimation of long-term costs. Future studies
could benefit from incorporating dynamic pricing models that account for drug price reductions
over time, especially as new generics or alternative therapies enter the market.
-The study uses conventional WTP thresholds ($50,000, $100,000, $150,000) to assess cost-
effectiveness. However, these thresholds may not fully capture the value of therapies for terminal
diseases like mPDAC, where treatment offers limited survival benefits but might significantly
improve patient's quality of life in the short term. Moreover, there is no universally accepted
WTP threshold in the US, making these values somewhat arbitrary.
Please review this paper.
user
Title: Cost-effectiveness of NALIRIFOX versus Nab-paclitaxel and Gemcitabine in Previously
Untreated Metastatic Pancreatic Ductal Adenocarcinoma
Version: 2 Date: 17 Mar 2025
Reviewer:  Anwar Ashraf Abouelnasr
Reviewer's report:
Dear Authors, please address the following points below
-The model assumes that patients who do not receive second-line therapy in either group receive
the best supportive care (BSC), which may not fully reflect the complexity of treatment decisions
or the potential for off-label or clinical trial participation. Additionally, the assumption of no
cost adjustment for half of the cycle in the first model cycle could be an oversimplification that
may affect the precision of cost estimates, especially in treatments with staggered administration
schedules.
-The analysis focuses solely on direct medical costs, excluding potential indirect costs such as
lost productivity or caregiver costs, which can be significant in cancer treatment. The inclusion
of indirect costs could provide a more comprehensive economic evaluation.
-The utility values used for progression-free survival (PFS), progression of disease (PD), and
mortality states (0.81, 0.73, and 0) are sourced from existing literature. However, these values
might not fully reflect patient experiences or preferences in the U.S., which could limit the
generalizability of the results. Additionally, disutility values related to adverse events (AEs) are
based on prior studies but could vary across populations or healthcare settings.
-The model extrapolates survival data from the NAPOLI 3 trial using Weibull and Gamma
distributions, but this can introduce some uncertainty, especially in extrapolating long-term
survival outcomes. The models assume similar rates of AE incidence in both treatment arms,
but there may be subtle differences in how AEs impact patients in real-world settings.
-Although the model uses data from the NAPOLI 3 trial and other relevant sources, it would
benefit from external validation using other cohorts or real-world data. This could help verify
the generalizability of the findings across different patient populations or healthcare settings.
-The model assumes a fixed cost and utility loss from grade #3 adverse events with an incidence
of #5%, but in practice, the severity and impact of these events can vary widely between
individuals. Including a more granular assessment of AE heterogeneity could improve the
model’s precision.
-While the study extrapolates long-term survival from Kaplan-Meier curves, it relies on trial data
that may not fully capture real-world treatment outcomes. Given that clinical trial participants
often do not represent the full spectrum of patients in the real world, additional data from
observational studies or real-world evidence would strengthen the study's findings.
-The assumption that treatment costs remain constant over time (without considering potential
price reductions or generics) might lead to an overestimation of long-term costs. Future studies
could benefit from incorporating dynamic pricing models that account for drug price reductions
over time, especially as new generics or alternative therapies enter the market.
-The study uses conventional WTP thresholds ($50,000, $100,000, $150,000) to assess cost-
effectiveness. However, these thresholds may not fully capture the value of therapies for terminal
diseases like mPDAC, where treatment offers limited survival benefits but might significantly
improve patient's quality of life in the short term. Moreover, there is no universally accepted
WTP threshold in the US, making these values somewhat arbitrary.
assistant