A comparison of partitioned survival analysis and state transition multi-state modelling approaches using a case study in oncology. (2nd October 2020)
- Record Type:
- Journal Article
- Title:
- A comparison of partitioned survival analysis and state transition multi-state modelling approaches using a case study in oncology. (2nd October 2020)
- Main Title:
- A comparison of partitioned survival analysis and state transition multi-state modelling approaches using a case study in oncology
- Authors:
- Cranmer, Holly
Shields, Gemma E.
Bullement, Ash - Abstract:
- Abstract: Aims: To construct and compare a partitioned-survival analysis (PartSA) and a semi-Markov multi-state model (MSM) to investigate differences in estimated cost effectiveness of a novel cancer treatment from a UK perspective. Materials and Methods: Data from a cohort of late-stage cancer patients ( N > 700) enrolled within a randomized, controlled trial were used to populate both modelling approaches. The statistical software R was used to fit parametric survival models to overall survival (OS) and progression-free survival (PFS) data to inform the PartSA (package "flexsurv"). The package "mstate" was used to estimate the MSM transitions (permitted transitions: (T1) "progression-free" to "dead", (T2) "post-progression" to "death", and (T3) "pre-progression" to "post-progression"). Key costs included were treatment-related (initial, subsequent, and concomitant), adverse events, hospitalizations and monitoring. Utilities were stratified by progression. Outcomes were discounted at 3.5% per annum over a 15-year time horizon. Results: The PartSA and MSM approaches estimated incremental cost-effectiveness ratios (ICERs) of £342, 474 and £411, 574, respectively. Scenario analyses exploring alternative parametric forms provided incremental discounted life-year estimates that ranged from +0.15 to +0.33 for the PartSA approach, compared with −0.13 to +0.23 for the MSM approach. This variation was reflected in the range of ICERs. The PartSA produced ICERs between £234, 829 andAbstract: Aims: To construct and compare a partitioned-survival analysis (PartSA) and a semi-Markov multi-state model (MSM) to investigate differences in estimated cost effectiveness of a novel cancer treatment from a UK perspective. Materials and Methods: Data from a cohort of late-stage cancer patients ( N > 700) enrolled within a randomized, controlled trial were used to populate both modelling approaches. The statistical software R was used to fit parametric survival models to overall survival (OS) and progression-free survival (PFS) data to inform the PartSA (package "flexsurv"). The package "mstate" was used to estimate the MSM transitions (permitted transitions: (T1) "progression-free" to "dead", (T2) "post-progression" to "death", and (T3) "pre-progression" to "post-progression"). Key costs included were treatment-related (initial, subsequent, and concomitant), adverse events, hospitalizations and monitoring. Utilities were stratified by progression. Outcomes were discounted at 3.5% per annum over a 15-year time horizon. Results: The PartSA and MSM approaches estimated incremental cost-effectiveness ratios (ICERs) of £342, 474 and £411, 574, respectively. Scenario analyses exploring alternative parametric forms provided incremental discounted life-year estimates that ranged from +0.15 to +0.33 for the PartSA approach, compared with −0.13 to +0.23 for the MSM approach. This variation was reflected in the range of ICERs. The PartSA produced ICERs between £234, 829 and £522, 963, whereas MSM results were more variable and included instances where the intervention was dominated and ICERs above £7 million (caused by very small incremental QALYs). Limitations and conclusions: Structural uncertainty in economic modelling is rarely explored due to time and resource limitations. This comparison of structural approaches indicates that the choice of structure may have a profound impact on cost-effectiveness results. This highlights the importance of carefully considered model conceptualization, and the need for further research to ascertain when it may be most appropriate to use each approach. … (more)
- Is Part Of:
- Journal of medical economics. Volume 23:Number 10(2020)
- Journal:
- Journal of medical economics
- Issue:
- Volume 23:Number 10(2020)
- Issue Display:
- Volume 23, Issue 10 (2020)
- Year:
- 2020
- Volume:
- 23
- Issue:
- 10
- Issue Sort Value:
- 2020-0023-0010-0000
- Page Start:
- 1176
- Page End:
- 1185
- Publication Date:
- 2020-10-02
- Subjects:
- Cost-effectiveness -- multi-state model -- partitioned survival -- decision-analytic model -- oncology
I00 -- D61 -- H51
Medical care -- Cost control -- Periodicals
Medical economics -- Periodicals
362.10941 - Journal URLs:
- http://informahealthcare.com/jme ↗
http://informahealthcare.com ↗ - DOI:
- 10.1080/13696998.2020.1796360 ↗
- Languages:
- English
- ISSNs:
- 1369-6998
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5017.049500
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 22948.xml