Modelling survival in hepatocellular carcinoma

Recommended Minimal Number of Harvested Lymph Nodes for Intrahepatic Cholangiocarcinoma

BACKGROUND

Lymph node (LN) metastasis is one factor indicating a poor prognosis after radical surgery for intrahepatic cholangiocarcinoma (ICC). Although several guidelines have recommended that LN dissection be strongly considered at the time of ICC surgery, no clear evidence regarding the appropriate number of harvested LNs has been established. Thus, we aimed to identify the minimum number of harvested LNs required for ICC by using a Bayesian Weibull model.

METHODS

Data from 142 patients who underwent radical hepatectomy (R0) for ICC from January 2000 to December 2018 were retrospectively reviewed. A Bayesian Weibull model was developed to analyze the effect of number of harvested LNs on survival of patients without (N0; n = 71) and with (N1; n = 71) metastatic nodes. We also compared the percentage of N1 patients (i.e., the N1 rate) in each of the five subgroups categorized according to the number of harvested LNs (1-4, 5-8, 9-12, 13-16, and ≥ 17).

RESULTS

In patients with 5 or more harvested LNs, the hazard ratio (HR) for LN metastasis was above the reference line (the HR with 5 harvested LNs, 1.95 (1.09-3.45)). The N1 rate of the 1-4 harvested LNs subgroup was lower than that of the other subgroups (e.g., 1-4 vs. 5-8; 16.1% vs. 39.4%, p = 0.014).

CONCLUSION

Our results suggest that at least 5 LNs should be harvested in patients who undergo radical surgery for ICC to promote accurate staging.

Cost-utility analysis of selective internal radiation therapy with Y-90 resin microspheres in hepatocellular carcinoma

Background: The study assessed the cost-utility of selective internal radiation therapy (SIRT) with Y-90 resin microspheres versus sorafenib in UK patients with unresectable hepatocellular carcinoma ineligible for transarterial chemoembolization. Materials & methods: A lifetime partitioned survival model was developed for patients with low tumor burden (≤25%) and good liver function (albumin-bilirubin grade 1). Efficacy, safety and quality of life data were from a European Phase III randomized controlled trial and published studies. Resource use was from registries and clinical surveys. Results: Discounted quality-adjusted life-years were 1.982 and 1.381, and discounted total costs were £29,143 and 30,927, for SIRT and sorafenib, respectively. Conclusion: SIRT has the potential to be a dominant (more efficacious/less costly) or cost-effective alternative to sorafenib in patients with unresectable hepatocellular carcinoma.

A Comparison of Different Analysis Methods for Reconstructed Survival Data to Inform Cost‑Effectiveness Analysis

OBJECTIVES

The aim of this study was to use Microsoft Excel spreadsheet software to fit parametric survival distributions. We also explain the differences between individual patient data (IPD) and survival data reconstructed in Excel and SAS.

METHODS

Three sets of patient data on overall survival were compared using different methods: 'original' IPD, 'reconstructed SAS', and 'reconstructed Excel'. The best-fit distribution was selected using visual observation, supported by linear plots of predicted probabilities, goodness-of-fit coefficients, and the sum of squared error of prediction. Outcomes included the incremental cost-effectiveness ratio (ICER), incremental net benefit (INB), incremental cost, and life-years gained over short-term and lifetime horizons. These were compared for different data sets.

RESULTS

In this example, log-normal, log-logistic, and Weibull distributions showed best-fit with the visual tests and goodness-of-fit statistics. Weibull and exponential distributions showed significant differences compared with IPD data. Data on short-term (5 years) time horizons produced by different data re-creation methods showed closeness with data reconstructed from SAS. The ICER and INB results were dependent on the time horizon and selected parametric distribution from the model.

CONCLUSIONS

Different approaches used in fitting parametric survival distributions yielded predicted probabilities that substantially differed from those using original IPD. Our study highlights the importance of following guidelines for economic evaluations with a systematic approach to parametric survival analysis techniques in order to select best fitting parametric survival distributions.

Mean overall survival gain with aflibercept plus FOLFIRI vs placebo plus FOLFIRI in patients with previously treated metastatic colorectal cancer

BACKGROUND

Mean survival in cancer trials can be estimated with statistical techniques to extrapolate study survival curves. This methodology was applied to data from the VELOUR trial, where use of the novel biologic aflibercept (ziv-aflibercept in the United States) in combination with fluorouracil+leucovorin+irinotecan (FOLFIRI), had significantly increased median overall survival (OS) by 1.44 months, vs placebo plus FOLFIRI in patients with metastatic colorectal cancer (mCRC) resistant to, or that had progressed following, an oxaliplatin-containing regimen.

METHODS

Parametric survival analyses were used to identify distributions with the best fit to the empirical VELOUR data. Mean OS for the two treatment groups (and pre-defined subgroups) was calculated from the fitted curves over a 15-year survival period.

RESULTS

Overall, the log-logistic distribution was the best-fitting for both treatment arms and, with it, the estimated difference in mean OS over 15 years between aflibercept+FOLFIRI and placebo+FOLFIRI was 4.7 months. In addition, the survival advantage with aflibercept was at least 3 months for the ITT population, whichever distribution was used to extrapolate survival.

CONCLUSION

Extrapolation of survival curves suggests the mean OS difference for aflibercept in the VELOUR trial is at least 3 months in the ITT population and selected subgroups.

Overview of parametric survival analysis for health-economic applications

Health economic models rely on data from trials to project the risk of events (e.g., death) over time beyond the span of the available data. Parametric survival analysis methods can be applied to identify an appropriate statistical model for the observed data, which can then be extrapolated to derive a complete time-to-event curve. This paper describes the properties of the most commonly used statistical distributions as a basis for these models and describes an objective process of identifying the most suitable parametric distribution in a given dataset. The approach can be applied with both individual-patient data as well as with survival probabilities derived from published Kaplan-Meier curves. Both are illustrated with analyses of overall survival from the Sorafenib Hepatocellular Carcinoma Assessment Randomised Protocol trial.