End points and statistical considerations in immuno-oncology trials: impact on multiple myeloma

Futility monitoring for randomized clinical trials with non-proportional hazards: An optimal conditional power approach

BACKGROUND

Standard futility analyses designed for a proportional hazards setting may have serious drawbacks when non-proportional hazards are present. One important type of non-proportional hazards occurs when the treatment effect is delayed. That is, there is little or no early treatment effect but a substantial later effect.

METHODS

We define optimality criteria for futility analyses in this setting and propose simple search procedures for deriving such rules in practice.

RESULTS

We demonstrate the advantages of the optimal rules over commonly used rules in reducing the average number of events, the average sample size, or the average study duration under the null hypothesis with minimal power loss under the alternative hypothesis.

CONCLUSION

Optimal futility rules can be derived for a non-proportional hazards setting that control the loss of power under the alternative hypothesis while maximizing the gain in early stopping under the null hypothesis.

Statistical considerations in long-term efficacy evaluation of anti-cancer therapies

Anti-cancer therapy has been a significant focus of research. Developing and marketing various types and mechanisms of anti-cancer therapies benefit a variety of patients significantly. The long-term benefit to patients in evaluating the risk-benefit ratio of anti-cancer therapy has become a significant concern. This paper discusses the evaluation of long-term efficacy within the estimand framework and summarizes the various strategies for addressing potential intercurrent events. Non-proportional hazards of survival data may arise with novel anti-cancer therapies, leading to potential bias in conventional evaluation methods. This paper reviews statistical methods for addressing this issue, including novel endpoints, hypothesis testing, and efficacy estimation methods. We also discuss the influences of treatment switching. Although advanced methods have been developed to address the non-proportional hazard, they still have limitations that require continued collaborative efforts to resolve issues.

Trial Design for Cancer Immunotherapy: A Methodological Toolkit

Immunotherapy with checkpoint inhibitors (CPIs) and cell-based products has revolutionized the treatment of various solid tumors and hematologic malignancies. These agents have shown unprecedented response rates and long-term benefits in various settings. These clinical advances have also pointed to the need for new or adapted approaches to trial design and assessment of efficacy and safety, both in the early and late phases of drug development. Some of the conventional statistical methods and endpoints used in other areas of oncology appear to be less appropriate in immuno-oncology. Conversely, other methods and endpoints have emerged as alternatives. In this article, we discuss issues related to trial design in the early and late phases of drug development in immuno-oncology, with a focus on CPIs. For early trials, we review the most salient issues related to dose escalation, use and limitations of tumor response and progression criteria for immunotherapy, the role of duration of response as an endpoint in and of itself, and the need to conduct randomized trials as early as possible in the development of new therapies. For late phases, we discuss the choice of primary endpoints for randomized trials, review the current status of surrogate endpoints, and discuss specific statistical issues related to immunotherapy, including non-proportional hazards in the assessment of time-to-event endpoints, alternatives to the Cox model in these settings, and the method of generalized pairwise comparisons, which can provide a patient-centric assessment of clinical benefit and be used to design randomized trials.

Treatment effect measures under nonproportional hazards

In a clinical trial with a time-to-event endpoint the treatment effect can be measured in various ways. Under proportional hazards all reasonable measures (such as the hazard ratio and the difference in restricted mean survival time) are consistent in the following sense: Take any control group survival distribution such that the hazard rate remains above zero; if there is no benefit by any measure there is no benefit by all measures, and as the magnitude of treatment benefit increases by any measure it increases by all measures. Under nonproportional hazards, however, survival curves can cross, and the direction of the effect for any pair of measures can be inconsistent. In this paper we critically evaluate a variety of treatment effect measures in common use and identify flaws with them. In particular, we demonstrate that a treatment's benefit has two distinct and independent dimensions which can be measured by the difference in the survival rate at the end of follow-up and the difference in restricted mean survival time, and that commonly used measures do not adequately capture both dimensions. We demonstrate that a generalized hazard difference, which can be estimated by the difference in exposure-adjusted subject incidence rates, captures both dimensions, and that its inverse, the number of patient-years of follow-up that results in one fewer event (the NYNT), is an easily interpretable measure of the magnitude of clinical benefit.

Finite Mixture Models, a Flexible Alternative to Standard Modeling Techniques for Extrapolated Mean Survival Times Needed for Cost-Effectiveness Analyses

OBJECTIVES

To compare finite mixture models with common survival models with respect to how well they fit heterogenous data used to estimate mean survival times required for cost-effectiveness analysis.

METHODS

Publicly available overall survival (OS) and progression-free survival (PFS) curves were digitized to produce nonproprietary data. Regression models based on the following distributions were fit to the data: Weibull, lognormal, log-logistic, generalized F, generalized gamma, Gompertz, mixture of 2 Weibulls, and mixture of 3 Weibulls. A second set of analyses was performed based on data in which patients who had not experienced an event by 30 months were censored. Model performance was compared based on the Akaike information criterion (AIC).

RESULTS

For PFS, the 3-Weibull mixture (AIC = 479.94) and 2-Weibull mixture (AIC = 488.24) models outperformed other models by more than 40 points and produced the most accurate estimates of mean survival times. For OS, the AIC values for all models were similar (all within 4 points). The means for the mixture 3-Weibulls mixture model (17.60 months) and the 2-Weibull mixture model (17.59 months) were the closest to the Kaplan-Meier mean estimate of (17.58 months). The results and conclusions from the censored analysis of PFS were similar to the uncensored PFS analysis. On the basis of extrapolated mean OS, all models produced estimates within 10% of the Kaplan-Meier mean survival time.

CONCLUSIONS

Finite mixture models offer a flexible modeling approach that has benefits over standard parametric models when analyzing heterogenous data for estimating survival times needed for cost-effectiveness analysis.

Immune checkpoint inhibitors in acute myeloid leukemia

Understanding the immune biology of AML and designing rational approaches to target or harness the immune environment to improve outcomes is an area of intense research in AML. There are two primary immune checkpoint harnessing modalities under clinical evaluation in AML: T-cell (such as PD1 inhibitors nivolumab and pembrolizumab) and macrophage (such as the anti-CD47 antibody magrolimab) These work synergistically with hypomethylating agents. Patients who do not achieve complete or partial responses based on IWG criteria often achieve durable stable disease or hematologic improvement, which may provide meaningful benefit for patients, even in the absence of traditional response unlike cytotoxic therapies. Patients should ideally be prospectively selected for CPI based therapies based on pre-treatment biomarkers, as there are definite populations that are more likely to respond. Immune toxicities are often mistaken for infection or other adverse event; however, if identified and treated early and aggressively with steroids, immune toxicity outcomes can be improved. Therefore, in the formative stage of development ideally only centers with experience in immune therapies should perform CPI studies in AML.

Evolving use of real-world evidence in the regulatory process: a focus on immuno-oncology treatment and outcomes

In recent years, regulatory bodies have increasingly recognized the utility of real-world evidence (RWE) for supplementing and supporting clinical trial data in new drug applications. Nevertheless, the integration of RWE into established regulatory processes is complex and the generation of 'regulatory-grade' real-world data faces operational, methodological, data-related and policy-related challenges. In parallel with this evolving role for RWE, immuno-oncology therapies have emerged as leading cancer treatments and are expected to continue to play a central role in the future. In this article, we review the current literature on the use of RWE for regulatory submissions, with a focus on novel anticancer immunotherapies, and discuss the utility and current limitations of RWE in the context of drug development and regulatory approvals.

Pembrolizumab plus lenalidomide and dexamethasone in treatment-naive multiple myeloma (KEYNOTE-185): subgroup analysis in Japanese patients

The global, randomized, open-label KEYNOTE-185 study closed early after an interim analysis showed an unfavorable benefit-risk profile with pembrolizumab plus lenalidomide and low-dose dexamethasone (Rd) versus Rd alone in treatment-naive, transplant-ineligible multiple myeloma. This subgroup analysis reported outcomes in the Japanese population. Patients were randomly assigned (1:1) to pembrolizumab plus Rd or Rd alone, stratified by age and International Staging System. The primary end point was progression-free survival (PFS). Fifty-two Japanese patients were randomly assigned to pembrolizumab plus Rd (n = 27) or Rd (n = 25). The median follow-up was 7.2 months (range, 0.4-13.8). The median PFS was not reached (NR); 6-month PFS was 91.2% versus 86.2% with pembrolizumab plus Rd versus Rd [hazard ratio (HR), 0.31; 95% CI, 0.06-1.63]. The median overall survival (OS) was NR; 6-month OS was 96.2% versus 95.7% with pembrolizumab plus Rd versus Rd (HR, 0.33; 95% CI, 0.03-3.72). With pembrolizumab plus Rd versus Rd, grade 3-5 adverse events occurred in 70.4% versus 69.6% of patients; serious adverse events occurred in 40.7% versus 52.5%. Although in the Japanese subgroup of KEYNOTE-185 adding pembrolizumab to Rd did not show an unfavorable risk-benefit, the analysis is limited by short follow-up and small sample size, affecting generalizability of the results.

Current challenges for assessing the long-term clinical benefit of cancer immunotherapy: a multi-stakeholder perspective

Immuno-oncologics (IOs) differ from chemotherapies as they prime the patient's immune system to attack the tumor, rather than directly destroying cancer cells. The IO mechanism of action leads to durable responses and prolonged survival in some patients. However, providing robust evidence of the long-term benefits of IOs at health technology assessment (HTA) submission presents several challenges for manufacturers. The aim of this article was to identify, analyze, categorize, and further explore the key challenges that regulators, HTA agencies, and payers commonly encounter when assessing the long-term benefits of IO therapies. Insights were obtained from an international, multi-stakeholder steering committee (SC) and expert panels comprising of payers, economists, and clinicians. The selected individuals were tasked with developing a summary of challenges specific to IOs in demonstrating their long-term benefits at HTA submission. The SC and expert panels agreed that standard methods used to assess the long-term benefit of anticancer drugs may have limitations for IO therapies. Three key areas of challenges were identified: (1) lack of a disease model that fully captures the mechanism of action and subsequent patient responses; (2) estimation of longer-term outcomes, including a lack of agreement on ideal methods of survival analyses and extrapolation of survival curves; and (3) data limitations at the time of HTA submission, for which surrogate survival end points and real-world evidence could prove useful. A summary of the key challenges facing manufacturers when submitting evidence at HTA submission was developed, along with further recommendations for manufacturers in what evidence to produce. Despite almost a decade of use, there remain significant challenges around how best to demonstrate the long-term benefit of checkpoint inhibitor-based IOs to HTA agencies, clinicians, and payers. Manufacturers can potentially meet or mitigate these challenges with a focus on strengthening survival analysis methodology. Approaches to doing this include identifying reliable biomarkers, intermediate and surrogate end points, and the use of real-world data to inform and validate long-term survival projections. Wider education across all stakeholders-manufacturers, payers, and clinicians-in considering the long-term survival benefit with IOs is also important.

ImmunoPET in Multiple Myeloma-What? So What? Now What?

Despite constant progress over the past three decades, multiple myeloma (MM) is still an incurable disease, and the identification of new biomarkers to better select patients and adapt therapy is more relevant than ever. Recently, the introduction of therapeutic monoclonal antibodies (mAbs) (including direct-targeting mAbs and immune checkpoint inhibitors) appears to have changed the paradigm of MM management, emphasizing the opportunity to cure MM patients through an immunotherapeutic approach. In this context, immuno-positron emission tomography (immunoPET), combining the high sensitivity and resolution of a PET camera with the specificity of a radiolabelled mAb, holds the capability to cement this new treatment paradigm for MM patients. It has the potential to non-invasively monitor the distribution of therapeutic antibodies or directly monitor biomarkers on MM cells, and to allow direct observation of potential changes over time and in response to various therapeutic interventions. Tumor response could, in the future, be anticipated more effectively to provide individualized treatment plans tailored to patients according to their unique imaging signatures. This work explores the important role played by immunotherapeutics in the management of MM, and focuses on some of the challenges for this drug class and the significant interest of companion imaging agents such as immunoPET.

Publicly accessible evidence of health-related quality of life benefits associated with cancer drugs approved by the European Medicines Agency between 2009 and 2015

OBJECTIVE

Health-related quality of life (HRQoL) is one of the most important patient-relevant study end-points for the direct measurement of the benefit of cancer drugs. Therefore, our aim is to detect cancer indications with no published information on HRQoL at the time of European Medicines Agency (EMA) approval and monitor any reported HRQoL evidence updates after at least three years of follow-up.

METHODS

We included all cancer indications that were approved by the EMA between January 2009 and October 2015. Our main sources of information were the EMA website, clinicaltrials.gov and a systematic literature search in PubMed. Information on HRQoL outcomes was extracted alongside evidence on median overall survival.

RESULTS

In total, we identified 110 indications, of which more than half (n = 58, 53%) were lacking available information on HRQoL assessments at the time of EMA approval. After a monitoring period of at least three years, 24 updates were identified, resulting in 34 (31%) therapies where information on HRQoL was still not available. For the 76 therapies with reported information on HRQoL, cancer-specific instruments were mostly used (n = 49/76). Regarding cumulative evidence on median overall survival and HRQoL, 33 (n = 33/110, 30%) as well as 15 (n = 15/110, 14%) cancer drugs were lacking information on both study end-points at the time of approval and after monitoring, respectively.

CONCLUSION

Our results demonstrate that there is an urgent need of routine re-evaluation of reimbursed cancer drugs with initially missing information on major outcomes. Standardisation of the typology and quality of HRQoL assessments need to be improved to allow better comparability of results.

Efficacy and safety of anticancer drug combinations: a meta-analysis of randomized trials with a focus on immunotherapeutics and gene-targeted compounds

Hundreds of trials are being conducted to evaluate combination of newer targeted drugs as well as immunotherapy. Our aim was to compare efficacy and safety of combination versus single non-cytotoxic anticancer agents. We searched PubMed (01/01/2001 to 03/06/2018) (and, for immunotherapy, ASCO and ESMO abstracts (2016 through March 2018)) for randomized clinical trials that compared a single non-cytotoxic agent (targeted, hormonal, or immunotherapy) versus a combination with another non-cytotoxic partner. Efficacy and safety endpoints were evaluated in a meta-analysis using a linear mixed-effects model (guidelines per PRISMA Report).We included 95 randomized comparisons (single vs. combination non-cytotoxic therapies) (59.4%, phase II; 41.6%, phase III trials) (29,175 patients (solid tumors)). Combinations most frequently included a hormonal agent and a targeted small molecule (23%). Compared to single non-cytotoxic agents, adding another non-cytotoxic drug increased response rate (odds ratio [OR]=1.61, 95%CI 1.40-1.84)and prolonged progression-free survival (hazard ratio [HR]=0.75, 95%CI 0.69-0.81)and overall survival (HR=0.87, 95%CI 0.81-0.94) (all p<0.001), which was most pronounced for the association between immunotherapy combinations and longer survival. Combinations also significantlyincreased the risk of high-grade toxicities (OR=2.42, 95%CI 1.98-2.97) (most notably for immunotherapy and small molecule inhibitors) and mortality at least possibly therapy related (OR: 1.33, 95%CI 1.15-1.53) (both p<0.001) (absolute mortality = 0.90% (single agent) versus 1.31% (combinations)) compared to single agents. In conclusion, combinations of non-cytotoxic drugs versus monotherapy in randomized cancer clinical trials attenuated safety, but increased efficacy, with the balance tilting in favor of combination therapy, based on the prolongation in survival.

Challenges and shifting paradigms in clinical trials in oncology: the case for immunological and targeted therapies

The advent of immunotherapy has undoubtedly changed the current standard for cancer treatment. Immunotherapy offers the possibility of achieving excellent results—a new alternative for patients with advanced-stage or relapsed disease. Nowadays, the progress made in tumour biology has led to multiple advances in clinical and translational cancer research. Many oncogenic pathways responsible for tumour growth and metastases have been described and, consequently, multiple new cancer therapeutic agents have been developed and are under current investigation. Due to this rapid increase in knowledge and pharmaceutical development, traditional clinical trials designs have encountered major limitations. The pharmacological differences (in toxicity profiles and effectiveness patterns) between immunotherapy and chemotherapy have caused traditional clinical trials to evolve in order to meet this emerging need. This review focuses on the different options pertaining to clinical trial design that have arisen in the field of immuno-oncology, as well as the challenges of accurately interpreting traditional survival analyses within this novel area of cancer medicine.

Comparison of Long-term Survival Benefits in Trials of Immune Checkpoint Inhibitor vs Non-Immune Checkpoint Inhibitor Anticancer Agents Using ASCO Value Framework and ESMO Magnitude of Clinical Benefit Scale

IMPORTANCE

Recently, anticancer agents have generated excitement owing to their capacity to preserve long-term durable survival in some patients who are represented by a tail of the survival curve. However, because traditional measures of clinical benefit may not accurately capture durable survival, amendments to various valuation frameworks have been proposed to capture this benefit.

OBJECTIVES

To determine how frequently immune checkpoint inhibitor (ICI) anticancer agents vs non-ICI anticancer agents displayed trends of long-term durable survival, as defined by the American Society of Clinical Oncology Value Framework version 2 (ASCO-VF v2) and European Society of Medical Oncology Magnitude of Clinical Benefit Scale version 1.1 (ESMO-MCBS v1.1), as well as to further analyze the degree of agreement between ASCO and ESMO frameworks.

DESIGN, SETTING, AND PARTICIPANTS

In this cohort study, anticancer agents from phase 2 or 3 randomized clinical trials (RCTs) cited for clinical efficacy evidence in drug approval by the US Food and Drug Administration between January 2011 and March 2018 were identified. Data required for the ASCO-VF v2 tail-of-the-curve bonus and the ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments were extracted from relevant RCTs. Frequency and difference in proportions were calculated to determine how often survival benefits were awarded to anticancer agents overall and to ICI and non-ICI anticancer agents individually.

MAIN OUTCOMES AND MEASURES

American Society of Clinical Oncology Value Framework v2 tail-of-the-curve bonuses and ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments.

RESULTS

In total, 247 RCTs were identified, and 100 RCTs involving 57 164 patients were included, with 14 examining ICI agents (1 ipilimumab, 5 pembrolizumab, 5 nivolumab, 2 atezolizumab, and 1 durvalumab) and 86 examining non-ICI agents (74 targeted therapy, 8 chemotherapy, 3 hormone therapy, and 1 radiopharmaceutical). Randomized clinical trials were awarded ASCO-VF v2 tail-of-the-curve bonuses more often than ESMO-MCBS v1.1 immunotherapy-triggered long-term plateau adjustments (ASCO-VF v2, 45.0% [8 of 14 ICI RCTs and 37 of 86 non-ICI RCTs] vs ESMO-MCBS v1.1, 2.6% [1 of 12 ICI RCTs and 1 of 66 non-ICI RCTs). Randomized clinical trials for ICIs were not more likely to receive an ASCO-VF v2 bonus or ESMO-MCBS v1.1 adjustment than non-ICI RCTs (ASCO-VF: risk difference, 0.14; 95% CI, -0.14 to 0.42; P = .32; ESMO-MCBS: risk difference, 0.07; 95% CI, -0.09 to 0.23; P = .40). Poor agreement was found between the framework algorithms in identifying long-term survival benefits from RCTs (κ = 0.01; 95% CI, -0.23 to 0.22; P = .50).

CONCLUSIONS AND RELEVANCE

The ASCO-VF v2 and ESMO-MCBS v1.1 may require additional refinement to accurately capture the benefit of durable long-term survival, or ICI agents may not preserve long-term survival as conventionally thought.

Elotuzumab plus lenalidomide and dexamethasone in relapsed/refractory multiple myeloma: Extended 4-year follow-up and analysis of relative progression-free survival from the randomized ELOQUENT-2 trial

BACKGROUND

The randomized phase 3 ELOQUENT-2 study (NCT01239797) evaluated the efficacy and safety of elotuzumab plus lenalidomide and dexamethasone (ELd) versus lenalidomide and dexamethasone (Ld) in relapsed/refractory multiple myeloma (RRMM), and to date, has the longest follow-up of any monoclonal antibody in patients with RRMM.

METHODS

In this extended 4-year follow-up of the ELOQUENT-2 trial, the coprimary endpoints of progression-free survival (PFS) and overall response rate as well as the secondary endpoint of overall survival were assessed. In the absence of head-to-head trials comparing Ld-based triplet regimens to guide treatment selection, 4 randomized controlled trials-ELOQUENT-2, ASPIRE, TOURMALINE-MM1, and POLLUX-were indirectly compared to provide insight into the relative efficacy of these regimens in RRMM.

RESULTS

Data at 4 years were consistent with 2- and 3-year follow-up data: ELd reduced the risk of disease progression/death by 29% versus Ld (hazard ratio, 0.71) while maintaining safety. The greatest PFS benefit among the assessed subgroups was observed in patients at the median time or further from diagnosis (≥3.5 years) with 1 prior line of therapy, who had a 44% reduction in the risk of progression/death, and in patients in the high-risk category, who had a 36% reduction in favor of ELd. This regimen also showed a relative PFS benefit that was maintained beyond 50 months.

CONCLUSIONS

The sustained PFS benefit and long-term safety of ELd at 4 years, similar to those observed at 2 and 3 years, support ELd as a valuable therapeutic option for the long-term treatment of patients with RRMM.

A Comparison of Response Patterns for Progression-Free Survival and Overall Survival Following Treatment for Cancer With PD-1 Inhibitors: A Meta-analysis of Correlation and Differences in Effect Sizes

IMPORTANCE

Based on efficacy results from pivotal randomized clinical trials, PD-1 (programmed cell death 1) inhibitors, such as nivolumab and pembrolizumab, have been approved to treat various cancers. Response patterns with varying effects on progression-free survival (PFS) and overall survival (OS) have been reported for these drugs.

OBJECTIVE

To compare 2 outcomes for PD-1 inhibitors: the correlation between PFS and OS and the differences in treatment effect size between PFS and OS.

DATA SOURCES

A systematic search of PubMed, Google Scholar, the Cochrane Library, Web of Science, and conference abstracts for randomized clinical trials of nivolumab and pembrolizumab published in English.

STUDY SELECTION

Randomized clinical trials of nivolumab or pembrolizumab in adults with solid-tissue cancers with a nonimmunotherapy control.

DATA EXTRACTION AND SYNTHESIS

Two reviewers screened the studies for selection and extracted data on medians and hazard ratios (HRs) for PFS and OS. A pooled meta-analysis was conducted.

MAIN OUTCOMES AND MEASURES

Across all trials, correlation coefficients between median PFS and median OS and between PFS benefit and OS benefit as well as the HRs of PFS and OS were assessed. The difference in treatment effect sizes between PFS and OS was assessed using a ratio of HRs (rHR). Subgroup analyses were conducted to observe differences based on drug, tumor type, and timing of therapy.

RESULTS

Ten randomized clinical trials that included 4653 patients and met inclusion criteria were identified, as were 2 others (comprising 764 patients) in which nivolumab or pembrolizumab was used following treatment with ipilimumab. The correlations between median PFS and median OS (r = 0.676; R2 = 0.457; P = .09) and the correlations between the change in PFS and the change in OS (r = 0.474; R2 = 0.225; P = .28) were not significant. However, the correlation between HRs of PFS and OS was significant (r = 0.637; R2 = 0.406; P = .048). Using random-effects meta-analysis, the protective effects of treatment were greater for OS than for PFS (pooled rHR, 1.18; 95% CI, 1.06-1.31; P = .002). There was no statistical evidence for heterogeneity across the studies (Q = 6.24; P = .72; I2 = 0%). Subgroup analyses showed some differences in the treatment effect sizes based on drug type, tumor type, and line of therapy.

CONCLUSIONS AND RELEVANCE

There was no significant correlation between OS and PFS in terms of medians and gains in medians, but their HRs were significantly correlated. The protective effects of treatment were greater for OS than for PFS. Traditional Response Evaluation Criteria in Solid Tumors-based PFS cannot capture the benefit of PD-1 inhibitors in patients with solid tumors, and OS should remain the gold standard.

Cancer treatment in the last 6 months of life: when inaction can outperform action

When an investigational anticancer drug is being tested, demonstration of improvement in overall survival (OS) will generally lead to regulatory approval. However, the value that improvement in OS adds to patients’ lives is guided largely by the context of the improvement and accompanying trade-offs. For example, when a patient’s life expectancy is less than 6 months, many oncologists will not embark on any active cancer treatments. However, multiple new anticancer drugs have been approved recently after being tested in end-stage cancer patients and demonstrating median OS in the experimental arm close to 6 months. Such practice, particularly when the treatment is also accompanied by serious toxicities and cost, can undermine a peaceful life-death transition. In this commentary, we review regulatory approvals in the last 5 years and the ethical considerations involved in testing active cancer treatment in terminal cancer patients.