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Recent discoveries in molecular diagnostics and drug treatments have improved the treatment of patients with advanced (inoperable) non-squamous non-small cell lung cancer (NSCLC) from solely platinum-based chemotherapy to more personalized treatment, including targeted therapies and immunotherapies. However, these improvements come at considerable costs, highlighting the need to assess their cost-effectiveness in order to optimize lung cancer care. Traditionally, costeffectiveness models for the evaluation of new lung cancer treatments were based on the findings of the randomized control trials (RCTs). However, the strict RCT inclusion criteria make RCT patients not representative of patients in the real-world. Patients in RCTs have a better prognosis than patients in a real-world setting. Therefore, in this study, we developed and validated a diagnosis-treatment decision model for patients with advanced (inoperable) non-squamous NSCLC based on real-world data in the Netherlands. The model is a patient-level microsimulation model implemented as discrete event simulation with five health events. Patients are simulated from diagnosis to death, including at most three treatment lines. The base-model (non-personalized strategy) was populated using real-world data of patients treated with platinum-based chemotherapy between 2008 and 2014 in one of six Dutch teaching hospitals. To simulate personalized care, molecular tumor characteristics were incorporated in the model based on the literature. The impact of novel targeted treatments and immunotherapies was included based on published RCTs. To validate the model, we compared survival under a personalized treatment strategy with observed real-world survival. This model can be used for health-care evaluation of personalized treatment for patients with advanced (inoperable) NSCLC in the Netherlands.

Background The risk of recurrence after resection of a stage II or III colon cancer, and therefore qualification for adjuvant chemotherapy (ACT), is traditionally based on clinicopathological parameters. However, the parameters used in clinical practice are not able to accurately identify all patients with or without minimal residual disease. Some patients considered ‘low-risk’ do develop recurrence (undertreatment), whilst other patients receiving ACT might not have developed recurrence at all (overtreatment). We previously analysed tumour tissue expression of 28 protein biomarkers that might improve identification of patients at risk of recurrence. In the present study we aimed to build a prognostic classifier based on these 28 biomarkers and clinicopathological parameters. Methods Classification and regression tree (CART) analysis was used to build a prognostic classifier based on a well described cohort of 386 patients with stage II and III colon cancer. Separate classifiers were built for patients who were or were not treated with ACT. Routine clinicopathological parameters and tumour tissue immunohistochemistry data were included, available for 28 proteins previously published. Classification trees were pruned until lowest misclassification error was obtained. Survival of the identified subgroups was analysed, and robustness of the selected CART variables was assessed by random forest analysis (1000 trees). Results In patients not treated with ACT, prognosis was estimated best based on expression of KCNQ1. Poor disease-free survival (DFS) was observed in those with loss of expression of KCNQ1 (HR = 3.38 (95% CI 2.12 – 5.40); p p p = 0.001). Conclusion KCNQ1 and LVI were identified as key features in prognostic classifiers for disease-free survival in stage II and III colon cancer patients.

Supplemental material, sj-pdf-1-mdm-10.1177_0272989X211016307 for Choosing a Metamodel of a Simulation Model for Uncertainty Quantification by Tiago M. de Carvalho, Joost van Rosmalen, Harold B. Wolff, Hendrik Koffijberg and Veerle M. H. Coupé in Medical Decision Making

Supplemental material, sj-pdf-1-mdm-10.1177_0272989X211016307 for Choosing a Metamodel of a Simulation Model for Uncertainty Quantification by Tiago M. de Carvalho, Joost van Rosmalen, Harold B. Wolff, Hendrik Koffijberg and Veerle M. H. Coupé in Medical Decision Making

Treatment decision-making for patients with incurable non-small cell lung cancer (NSCLC) is complex due to the rapidly increasing number of treatments and discovery of new biomarkers. Decision support systems (DSS) could assist thoracic oncologists (TO) weighing of the pros and cons of treatments in order to arrive at an evidence-based and personalized treatment advice. Our aim is to inventory (1) TO’s needs with regard to DSS in the treatment of incurable (stage IIIB/IV) NSCLC patients, and (2) preferences regarding the development of future tools in this field. We disseminated an online inventory questionnaire among all members of the Section of Oncology within the Society of Physicians in Chest Medicine and Tuberculosis. Telephone interviews were conducted to better contextualize the findings from the questionnaire. In total, 58 TO completed the questionnaire and expressed a need for new DSS. They reported that it is important for tools to include genetic and immune markers, to be sufficiently validated, regularly updated, and time-efficient. Also, future DSS should incorporate multiple treatment options, integrate estimates of toxicity, quality of life and cost-effectiveness of treatments, enhance communication between caregivers and patients, and use IT solutions for a clear interface and continuous updating of tools. With this inventory among Dutch TO, we summarized the need for new DSS to aid treatment decision-making for patients with incurable NSCLC. To meet the expressed needs, substantial additional efforts will be required by DSS developers, above already existing tools.

Supplemental material, sj-docx-1-mdm-10.1177_0272989X211016307 for Choosing a Metamodel of a Simulation Model for Uncertainty Quantification by Tiago M. de Carvalho, Joost van Rosmalen, Harold B. Wolff, Hendrik Koffijberg and Veerle M. H. Coupé in Medical Decision Making

Supplemental material, sj-pdf-1-tag-10.1177_1756284821995715 for Model-based effectiveness and cost-effectiveness of risk-based selection strategies for adjuvant chemotherapy in Dutch stage II colon cancer patients by Gabrielle Jongeneel, Marjolein J. E. Greuter, Felice N. van Erning, Miriam Koopman, Geraldine R. Vink, Cornelis J. A. Punt and Veerle M. H. Coupé in Therapeutic Advances in Gastroenterology

There is currently no consensus regarding preferred clinical outcome measures following image-guided tumor ablation or clear definitions of oncologic end points. This consensus document proposes standardized definitions for a broad range of oncologic outcome measures with recommendations on how to uniformly document, analyze, and report outcomes. The initiative was coordinated by the Society of Interventional Oncology in collaboration with the Definition for the Assessment of Time-to-Event End Points in Cancer Trials, or DATECAN, group. According to predefined criteria, based on experience with clinical trials, an international panel of 62 experts convened. Recommendations were developed using the validated three-step modified Delphi consensus method. Consensus was reached on when to assess outcomes per patient, per session, or per tumor; on starting and ending time and survival time definitions; and on time-to-event end points. Although no consensus was reached on the preferred classification system to report complications, quality of life, and health economics issues, the panel did agree on using the most recent version of a validated patient-reported outcome questionnaire. This article provides a framework of key opinion leader recommendations with the intent to facilitate a clear interpretation of results and standardize worldwide communication. Widespread adoption will improve reproducibility, allow for accurate comparisons, and avoid misinterpretations in the field of interventional oncology research. Published under a CC BY 4.0 license. Online supplemental material is available for this article. See also the editorial by Liddell in this issue.

Supplemental material, sj-pdf-1-tag-10.1177_1756284821995715 for Model-based effectiveness and cost-effectiveness of risk-based selection strategies for adjuvant chemotherapy in Dutch stage II colon cancer patients by Gabrielle Jongeneel, Marjolein J. E. Greuter, Felice N. van Erning, Miriam Koopman, Geraldine R. Vink, Cornelis J. A. Punt and Veerle M. H. Coupé in Therapeutic Advances in Gastroenterology

Supplemental material, sj-pdf-1-mdm-10.1177_0272989X20978167 for Cost-Effectiveness of Surveillance Scanning Strategies after Curative Treatment of Non–Small-Cell Lung Cancer by Henri B. Wolff, Leonie Alberts, Elisabeth A. Kastelijn, Sherif Y. El Sharouni, Franz M. N. H. Schramel and Veerle M. H. Coupé in Medical Decision Making

Supplemental material, Figure_3_(1) for Validation of Microsimulation Models against Alternative Model Predictions and Long-Term Colorectal Cancer Incidence and Mortality Outcomes of Randomized Controlled Trials by Jie-Bin Lew, Marjolein J. E. Greuter, Michael Caruana, Emily He, Joachim Worthington, D. James St John, Finlay A. Macrae, Eleonora Feletto, Veerle M. H. Coupé and Karen Canfell in Medical Decision Making

Supplemental material, sj-pdf-1-mdm-10.1177_0272989X20978167 for Cost-Effectiveness of Surveillance Scanning Strategies after Curative Treatment of Non–Small-Cell Lung Cancer by Henri B. Wolff, Leonie Alberts, Elisabeth A. Kastelijn, Sherif Y. El Sharouni, Franz M. N. H. Schramel and Veerle M. H. Coupé in Medical Decision Making

Supplemental material, Figure_1_(1) for Validation of Microsimulation Models against Alternative Model Predictions and Long-Term Colorectal Cancer Incidence and Mortality Outcomes of Randomized Controlled Trials by Jie-Bin Lew, Marjolein J. E. Greuter, Michael Caruana, Emily He, Joachim Worthington, D. James St John, Finlay A. Macrae, Eleonora Feletto, Veerle M. H. Coupé and Karen Canfell in Medical Decision Making

Supplemental material, Figure_2_(1) for Validation of Microsimulation Models against Alternative Model Predictions and Long-Term Colorectal Cancer Incidence and Mortality Outcomes of Randomized Controlled Trials by Jie-Bin Lew, Marjolein J. E. Greuter, Michael Caruana, Emily He, Joachim Worthington, D. James St John, Finlay A. Macrae, Eleonora Feletto, Veerle M. H. Coupé and Karen Canfell in Medical Decision Making

Supplemental material, Model_validation(SSL)_Appendix_online_supp for Validation of Microsimulation Models against Alternative Model Predictions and Long-Term Colorectal Cancer Incidence and Mortality Outcomes of Randomized Controlled Trials by Jie-Bin Lew, Marjolein J. E. Greuter, Michael Caruana, Emily He, Joachim Worthington, D. James St John, Finlay A. Macrae, Eleonora Feletto, Veerle M. H. Coupé and Karen Canfell in Medical Decision Making

The Australian National Bowel Cancer Screening Program (NBCSP) will fully roll-out 2-yearly screening using the immunochemical Faecal Occult Blood Testing (iFOBT) in people aged 50 to 74 years by 2020. In this study, we aimed to estimate the comparative health benefits, harms, and cost-effectiveness of screening with iFOBT, versus other potential alternative or adjunctive technologies. A comprehensive validated microsimulation model, Policy1-Bowel, was used to simulate a total of 13 screening approaches involving use of iFOBT, colonoscopy, sigmoidoscopy, computed tomographic colonography (CTC), faecal DNA (fDNA) and plasma DNA (pDNA), in people aged 50 to 74 years. All strategies were evaluated in three scenarios: (i) perfect adherence, (ii) high (but imperfect) adherence, and (iii) low adherence. When assuming perfect adherence, the most effective strategies involved using iFOBT (annually, or biennially with/without adjunct sigmoidoscopy either at 50, or at 54, 64 and 74 years for individuals with negative iFOBT), or colonoscopy (10-yearly, or once-off at 50 years combined with biennial iFOBT). Colorectal cancer incidence (mortality) reductions for these strategies were 51-67(74-80)% in comparison with no screening; 2-yearly iFOBT screening (i.e. the NBCSP) would be associated with reductions of 51(74)%. Only 2-yearly iFOBT screening was found to be cost-effective in all scenarios in context of an indicative willingness-to-pay threshold of A$50,000/life-year saved (LYS); this strategy was associated with an incremental cost-effectiveness ratio of A$2,984/LYS-A$5,981/LYS (depending on adherence). The fully rolled-out NBCSP is highly cost-effective, and is also one of the most effective approaches for bowel cancer screening in Australia.

OBJECTIVE: To investigate the individual and combined prognostic value of HIF1α, SLC2A1, and vascular endothelial growth factor A (VEGFA) in a multi-institutional cohort of patients with resected colorectal cancer liver metastasis (CRCLM). BACKGROUND: In the majority of patients with CRCLM, resection seems not to be curative, despite its curative intent. Overexpression of hypoxia-inducible factor 1α (HIF1α), glucose transporter 1 (SLC2A1; also known as GLUT1), and VEGFA has been associated with tumor progression and poor prognosis of patients with colorectal cancer (CRC). METHODS: Tissue microarrays were generated using CRCLM and patient-matched primary CRC from patients who underwent CRCLM resection between 1990 and 2010. Prognostic value of HIF1α, SLC2A1, and VEGFA was determined by immunohistochemistry. A 500-fold cross-validated hazard rate ratio (HRRav) for overall survival was calculated. RESULTS: HIF1α, SLC2A1, and VEGFA expression could be evaluated in 328, 350, and 335 patients, respectively. High SLC2A1 expression was associated with good prognosis (HRRav, 0.67; P (HRR >1) < 0.01) and high VEGFA expression to poor prognosis (HRRav, 1.84; P (HRR < 1) = 0.02), also after multivariate analysis including established clinicopathological prognostic variables (HRRav, 0.67; P (HRR > 1) < 0.01 and HRRav, 1.50; P (HRR < 1) = 0.02, respectively). SLC2A1 showed prognostic value particularly in patients treated with systemic therapy (P < 0.01), whereas the prognostic value of VEGFA expression was mainly observed in patients not treated with systemic therapy (P < 0.01). Prognosis was especially poor in patients with both low SLC2A1 and high VEGFA expression (P < 0.01). HIF1α expression was not associated with survival. CONCLUSIONS: SLC2A1 and VEGFA expression are prognostic molecular biomarkers for patients with CRCLM with added value to established clinicopathological variables.

OBJECTIVE: To investigate the individual and combined prognostic value of HIF1α, SLC2A1, and vascular endothelial growth factor A (VEGFA) in a multi-institutional cohort of patients with resected colorectal cancer liver metastasis (CRCLM). BACKGROUND: In the majority of patients with CRCLM, resection seems not to be curative, despite its curative intent. Overexpression of hypoxia-inducible factor 1α (HIF1α), glucose transporter 1 (SLC2A1; also known as GLUT1), and VEGFA has been associated with tumor progression and poor prognosis of patients with colorectal cancer (CRC). METHODS: Tissue microarrays were generated using CRCLM and patient-matched primary CRC from patients who underwent CRCLM resection between 1990 and 2010. Prognostic value of HIF1α, SLC2A1, and VEGFA was determined by immunohistochemistry. A 500-fold cross-validated hazard rate ratio (HRRav) for overall survival was calculated. RESULTS: HIF1α, SLC2A1, and VEGFA expression could be evaluated in 328, 350, and 335 patients, respectively. High SLC2A1 expression was associated with good prognosis (HRRav, 0.67; P (HRR >1) < 0.01) and high VEGFA expression to poor prognosis (HRRav, 1.84; P (HRR < 1) = 0.02), also after multivariate analysis including established clinicopathological prognostic variables (HRRav, 0.67; P (HRR > 1) < 0.01 and HRRav, 1.50; P (HRR < 1) = 0.02, respectively). SLC2A1 showed prognostic value particularly in patients treated with systemic therapy (P < 0.01), whereas the prognostic value of VEGFA expression was mainly observed in patients not treated with systemic therapy (P < 0.01). Prognosis was especially poor in patients with both low SLC2A1 and high VEGFA expression (P < 0.01). HIF1α expression was not associated with survival. CONCLUSIONS: SLC2A1 and VEGFA expression are prognostic molecular biomarkers for patients with CRCLM with added value to established clinicopathological variables.