Cancer patient survival can be parametrized to improve trial precision and reveal time-dependent therapeutic effects

A Model of Intratumor and Interpatient Heterogeneity Explains Clinical Trials of Curative Combination Therapy for Lymphoma

SIGNIFICANCE

A new model of intratumor and interpatient heterogeneity in response to drug combinations explains and predicts the results of clinical trials of curative-intent treatments for DLBCL. This model can be used to understand and inform optimal design of curative drug combinations and clinical trials. See related commentary by Goldstein et al., p. 153.

Loss of survivorship in nasopharyngeal carcinoma attributable to fine particulate matter and its constituents

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a prevalent malignant tumor in East Asia, particularly impacting China. The association between multiple constituents of fine particulate matter (PM2.5) and the survival time of NPC patients remains unclear, which poses a challenge for targeted public health interventions.

METHODS

An accelerated failure-time model with a 12-year cohort design was used to analyze the impact of long-term PM2.5 and its constituents on the survival time of 1492 NPC patients. Restricted cubic splines (RCS) functions and stratification analyses were conducted to identify the exposure-response curve and vulnerable subgroups, respectively.

RESULTS

PM2.5 and its constituents were significantly associated with reduced survival time in NPC patients. For per interquartile range (IQR) increase in concentrations, the time ratio changing percentage (TRCP) ranged from -28.8 % to -33.6 % for PM2.5, -34.7 % to -39.6 % for black carbon (BC), -13.6 % to -17.4 % for nitrate (NO3-), -21.9 % to -26.6 % for ammonium (NH4+), -29.5 % to -35.5 % for organic matter (OM), and -31.5 % to -36.2 % for sulfate (SO42-). The exposure-response relationship exhibited a nonlinear trend, with a steep slope at lower concentrations. Furthermore, females, patients with lower monocyte levels, and those with a drinking history faced a higher risk of reduced survival time.

CONCLUSIONS

The study reveals the urgent need for environmental regulations to mitigate PM2.5 and its constituents, particularly BC. The evidence of accelerated loss of survivorship is crucial for establishing air quality guidelines concerning PM constituents and formulating public health interventions and protective measures for high-risk NPC patients.

A simulated trial with reinforcement learning for the efficacy of Irinotecan and Ifosfamide versus Topotecan in relapsed, extensive stage small cell lung cancer

OBJECTIVES

Synthetic data may proxy clinical data. At the absence of direct clinical data, this study aimed to compare Irinotecan and Ifosfamide (II) with Topotecan in synthetic, recurrent small cell lung cancer (SCLC) patients within a simulated clinical trial.

MATERIALS AND METHODS

Two simulation stages were conducted. Initially, 200 recurrent SCLC cases were simulated to replicate a previous phase 3 trial, testing the utility of Cox proportional hazards model and simulation methodology together, where patients were randomized to receive Cyclophosphamide, Adriamycin, Vincristine (CAV) or Topotecan. In the second stage, 600 recurrent SCLC patients were simulated and randomized to compare Topotecan versus II in terms of overall survival (OAS), using Reinforcement Learning (RL) and Cox proportional hazards model.

RESULTS

CAV versus Topotecan comparison showed no statistical difference in overall survival (hazard ratio (HR): 0.89, 95% CI: 0.67-1.18, P = 0.418), aligning with the original clinical trial. For the Topotecan versus II comparison, the RL framework significantly favored the II arm (mean reward points: 193.43 versus - 251.82, permutation P < 0.0001). Likewise, II arm exhibited superior median OAS compared to Topotecan arm (11.12 versus 6.30 months). HR was 0.44 (95% CI: 0.38-0.52) with P < 0.0001, in favor of II.

CONCLUSION

Artificial trial results for CAV versus Topotecan matched the original trial, confirming indifference of OAS. Additionally, II yielded superior overall survival compared to Topotecan in recurrent SCLC patients. These demonstrate the potential of RL and simulation in conjunction with Cox modelling for similar studies. However, definitive conclusions necessitate a randomized clinical trial between II and Topotecan in this patient cohort.

Cost-effectiveness analysis of durvalumab plus tremelimumab as first-line therapy in patients with unresectable hepatocellular carcinoma

Background

The HIMALAYA trial found that durvalumab plus tremelimumab significantly prolonged progression-free survival and overall survival in patients with unresectable hepatocellular carcinoma (HCC) compared with sorafenib.

Objective

This study aimed to investigate the cost-effectiveness of durvalumab plus tremelimumab compared with sorafenib in the first-line HCC setting.

Design

A Markov model-based cost-effectiveness analysis.

Methods

We created a Markov model to compare healthcare costs and clinical outcomes of HCC patients treated with durvalumab plus tremelimumab in the first-line setting compared with sorafenib. We estimated transition probabilities from randomized trials. Lifetime direct healthcare costs, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratios were calculated for first-line durvalumab plus tremelimumab compared with sorafenib from a US payer's perspective.

Results

In the base case, first-line durvalumab plus tremelimumab was associated with an improvement of 0.29 QALYs compared with sorafenib. While both treatment strategies were associated with considerable lifetime expenditures, first-line durvalumab plus tremelimumab was less expensive than sorafenib ($188,405 vs $218,584). The incremental net monetary benefit for durvalumab plus tremelimumab versus sorafenib was $72,762 (valuing QALYs at $150,000 each). The results of durvalumab plus tremelimumab were better in terms of costs and health outcomes in patients with HBV-related HCC and high alpha-fetoprotein levels.

Conclusion

First-line durvalumab plus tremelimumab was estimated to be dominant for the treatment of unresectable HCC compared with sorafenib from a US payer's perspective.

Comprehensive approaches to preclinical evaluation of monoclonal antibodies and their next-generation derivatives

Biotherapeutics hold great promise for the treatment of several diseases and offer innovative possibilities for new treatments that target previously unaddressed medical needs. Despite successful transitions from preclinical to clinical stages and regulatory approval, there are instances where adverse reactions arise, resulting in product withdrawals. As a result, it is essential to conduct thorough evaluations of safety and effectiveness on an individual basis. This article explores current practices, challenges, and future approaches in conducting comprehensive preclinical assessments to ensure the safety and efficacy of biotherapeutics including monoclonal antibodies, toxin-conjugates, bispecific antibodies, single-chain antibodies, Fc-engineered antibodies, antibody mimetics, and siRNA-antibody/peptide conjugates.

Modelling the spatial risk pattern of dementia in Denmark using residential location data: A registry-based national cohort

Dementia is a major global public health concern that is increasingly leading to morbidity and mortality among older adults. While studies have focused on the risk factors and care provision, there is currently limited knowledge about the spatial risk pattern of the disease. In this study, we employ Bayesian spatial modelling with a stochastic partial differential equation (SPDE) approach to model the spatial risk using complete residential history data from the Danish population and health registers. The study cohort consisted of 1.6 million people aged 65 years and above from 2005 to 2018. The results of the spatial risk map indicate high-risk areas in Copenhagen, southern Jutland and Funen. Individual socioeconomic factors and population density reduce the intensity of high-risk patterns across Denmark. The findings of this study call for the critical examination of the contribution of place of residence in the susceptibility of the global ageing population to dementia.

Weibull parametric model for survival analysis in women with endometrial cancer using clinical and T2-weighted MRI radiomic features

BACKGROUND

Semiparametric survival analysis such as the Cox proportional hazards (CPH) regression model is commonly employed in endometrial cancer (EC) study. Although this method does not need to know the baseline hazard function, it cannot estimate event time ratio (ETR) which measures relative increase or decrease in survival time. To estimate ETR, the Weibull parametric model needs to be applied. The objective of this study is to develop and evaluate the Weibull parametric model for EC patients' survival analysis.

METHODS

Training (n = 411) and testing (n = 80) datasets from EC patients were retrospectively collected to investigate this problem. To determine the optimal CPH model from the training dataset, a bi-level model selection with minimax concave penalty was applied to select clinical and radiomic features which were obtained from T2-weighted MRI images. After the CPH model was built, model diagnostic was carried out to evaluate the proportional hazard assumption with Schoenfeld test. Survival data were fitted into a Weibull model and hazard ratio (HR) and ETR were calculated from the model. Brier score and time-dependent area under the receiver operating characteristic curve (AUC) were compared between CPH and Weibull models. Goodness of the fit was measured with Kolmogorov-Smirnov (KS) statistic.

RESULTS

Although the proportional hazard assumption holds for fitting EC survival data, the linearity of the model assumption is suspicious as there are trends in the age and cancer grade predictors. The result also showed that there was a significant relation between the EC survival data and the Weibull distribution. Finally, it showed that Weibull model has a larger AUC value than CPH model in general, and it also has smaller Brier score value for EC survival prediction using both training and testing datasets, suggesting that it is more accurate to use the Weibull model for EC survival analysis.

CONCLUSIONS

The Weibull parametric model for EC survival analysis allows simultaneous characterization of the treatment effect in terms of the hazard ratio and the event time ratio (ETR), which is likely to be better understood. This method can be extended to study progression free survival and disease specific survival.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03543215, https://clinicaltrials.gov/ , date of registration: 30th June 2017.

Bayesian meta-analysis of penetrance for cancer risk

Multi-gene panel testing allows many cancer susceptibility genes to be tested quickly at a lower cost making such testing accessible to a broader population. Thus, more patients carrying pathogenic germline mutations in various cancer-susceptibility genes are being identified. This creates a great opportunity, as well as an urgent need, to counsel these patients about appropriate risk-reducing management strategies. Counseling hinges on accurate estimates of age-specific risks of developing various cancers associated with mutations in a specific gene, ie, penetrance estimation. We propose a meta-analysis approach based on a Bayesian hierarchical random-effects model to obtain penetrance estimates by integrating studies reporting different types of risk measures (eg, penetrance, relative risk, odds ratio) while accounting for the associated uncertainties. After estimating posterior distributions of the parameters via a Markov chain Monte Carlo algorithm, we estimate penetrance and credible intervals. We investigate the proposed method and compare with an existing approach via simulations based on studies reporting risks for two moderate-risk breast cancer susceptibility genes, ATM and PALB2. Our proposed method is far superior in terms of coverage probability of credible intervals and mean square error of estimates. Finally, we apply our method to estimate the penetrance of breast cancer among carriers of pathogenic mutations in the ATM gene.

Imputation of Missing Data for Time-to-Event Endpoints Using Retrieved Dropouts

We have explored several statistical approaches to impute missing time-to-event data that arise from outcome trials with relatively long follow-up periods. Aligning with the primary estimand, such analyses evaluate the robustness of results by imposing an assumption different from censoring at random (CAR). Although there have been debates over which assumption and which method is more appropriate to be applied to the imputation, we propose to use the collection of retrieved dropouts as the basis of missing data imputation. As retrieved dropouts share a similar disposition, such as treatment discontinuation, with subjects who have missing data, they can reasonably be assumed to characterize the distribution of time-to-event among subjects with missing data. In terms of computational intensity and robustness to violation of underlying distributional assumption, we have compared parametric approaches via MCMC or MLE multivariate sampling procedures to a non-parametric bootstrap approach with respect to baseline hazard function. Each of these approaches follows a process of multiple imputation ("proper imputations"), analysis of complete datasets, and final combination. The type-I error, and power rates are examined under a wide range of scenarios to inform the performance characteristics. A subset of a real unblinded phase III CVOT is used to demonstrate the application of the proposed approaches, compared to the Cox proportional hazards model and jump-to-reference multiple imputation.

The heterogeneous impact of targeted therapy on the prognosis of stage III/IV colorectal cancer patients with different subtypes of TP53 mutations

BACKGROUND

The relationship between molecular characteristics and the prognosis of colorectal cancer (CRC) patients has not been fully understood. This study explored the impact of targeted therapy on the prognosis of CRC patients with different TP53 mutations, in the context of comprehensive treatment.

METHODS

This study included patients with stage III/IV primary CRC from the electronic medical record system. TP53 mutations were detected via next-generation sequencing (NGS) using formalin-fixed paraffin-embedded (FFPE) tissues. Applying two methods, we classified TP53 mutations as gain of function (GOF)/non-GOF mutations or known/likely loss of function (LOF) mutations. Kaplan-Meier plot and parametric survival analysis were performed to evaluate the prognosis of CRC patients and identify potential predictors.

RESULTS

There were 286 patients included, of which 166 (58.04%) patients received targeted therapy and 120 (41.96%) did not. There were 286 patients in the TP53 GOF classification set and 247 in the TP53 LOF classification set. Parametric survival analysis, adjusted for sex, onset, KRAS mutation, sidedness, stage, and surgery, showed that receiving targeted therapy predicted better overall survival (OS) among patients who harbored TP53 GOF mutations (HR 0.40, 95% confidence interval (CI) [0.21, 0.76], p = 0.005) or known LOF mutations (HR 0.21, 95% CI [0.07, 0.60], p = 0.002). However, there was no significant impact of receiving targeted therapy on OS among patients harboring TP53 non-GOF mutations (HR 1.68, 95% CI [0.50, 5.63], p = 0.403) or likely LOF mutations (HR 0.90, 95% CI [0.34, 2.39], p = 0.837).

CONCLUSIONS

Receiving targeted therapy had a heterogeneous impact on the prognosis of CRC patients harboring different TP53 mutations. These results provide promising value for future personalized treatment and precision medicine.

Additivity predicts the efficacy of most approved combination therapies for advanced cancer

Most advanced cancers are treated with drug combinations. Rational design aims to identify synergistic combinations, but existing synergy metrics apply to preclinical, not clinical data. Here we propose a model of drug additivity for progression-free survival (PFS) to assess whether clinical efficacies of approved drug combinations are additive or synergistic. This model includes patient-to-patient variability in best single-drug response plus the weaker drug per patient. Among US Food and Drug Administration approvals of drug combinations for advanced cancers (1995-2020), 95% exhibited additive or less than additive effects on PFS times. Among positive or negative phase 3 trials published between 2014-2018, every combination that improved PFS was expected to succeed by additivity (100% sensitivity) and most failures were expected to fail (78% specificity). This study shows synergy is neither a necessary nor common property of clinically effective drug combinations. The predictable efficacy of approved combinations suggests that additivity can be a design principle for combination therapies.

Robotic Versus Conventional Minimally Invasive Esophagectomy for Esophageal Cancer: A Meta-analysis

OBJECTIVES

To give a comprehensive review of the literature comparing perioperative outcomes and long-term survival with robotic-assisted minimally invasive esophagectomy (RAMIE) versus minimally invasive esophagectomy (MIE) for esophageal cancer.

BACKGROUND

Curative minimally invasive surgical treatment for esophageal cancer includes RAMIE and conventional MIE. It remains controversial whether RAMIE is comparable to MIE.

METHODS

This review was registered at the International Prospective Register of Systematic Reviews (CRD42021260963). A systematic search of databases was conducted. Perioperative outcomes and long-term survival were analyzed and subgroup analysis was conducted. Cumulative meta-analysis was performed to track therapeutic effectiveness.

RESULTS

Eighteen studies were included and a total of 2932 patients (92.88% squamous cell carcinoma, 29.83% neoadjuvant therapy, and 38.93% stage III-IV), 1418 underwent RAMIE and 1514 underwent MIE, were analyzed. The number of total lymph nodes (LNs) [23.35 (95% CI: 21.41-25.29) vs 21.98 (95% CI: 20.31-23.65); mean difference (MD) = 1.18; 95% CI: 0.06-2.30; P =0.04], abdominal LNs [9.05 (95% CI: 8.16-9.94) vs 7.75 (95% CI: 6.62-8.88); MD = 1.04; 95% CI: 0.19-1.89; P =0.02] and LNs along the left recurrent laryngeal nerve [1.74 (95% CI: 1.04-2.43) vs 1.34 (95% CI: 0.32-2.35); MD = 0.22; 95% CI: 0.09-0.35; P <0.001] were significantly higher in the RAMIE group. RAMIE is associated with a lower incidence of pneumonia [9.61% (95% CI: 7.38%-11.84%) vs 14.74% (95% CI: 11.62%-18.15%); odds ratio = 0.73; 95% CI: 0.58-0.93; P =0.01]. Meanwhile, other perioperative outcomes, such as operative time, blood loss, length of hospital stay, 30/90-day mortality, and R0 resection, showed no significant difference between the two groups. Regarding long-term survival, the 3-year overall survival was similar in the two groups, whereas patients undergoing RAMIE had a higher rate of 3-year disease-free survival compared with the MIE group [77.98% (95% CI: 72.77%-82.43%) vs 70.65% (95% CI: 63.87%-77.00%); odds ratio = 1.42; 95% CI: 1.11-1.83; P =0.006]. A cumulative meta-analysis conducted for each outcome demonstrated relatively stable effects in the two groups. Analyses of each subgroup showed similar overall outcomes.

CONCLUSIONS

RAMIE is a safe and feasible alternative to MIE in the treatment of resectable esophageal cancer with comparable perioperative outcomes and seems to indicate a possible superiority in LNs dissection in the abdominal cavity, and LNs dissected along the left recurrent laryngeal nerve and 3-year disease-free survival in particular in esophageal squamous cell carcinoma. Further randomized studies are needed to better evaluate the long-term benefits of RAMIE compared with MIE.

Drug independence and the curability of cancer by combination chemotherapy

Combination chemotherapy can cure certain leukemias and lymphomas, but most solid cancers are only curable at early stages. We review quantitative principles that explain the benefits of combining independently active cancer therapies in both settings. Understanding the mechanistic principles underlying curative treatments, including those developed many decades ago, is valuable for improving future combination therapies. We discuss contemporary evidence for long-established but currently neglected ideas of how combination therapy overcomes tumor heterogeneity. We show that a unified model of interpatient and intratumor heterogeneity describes historical progress in the treatment of pediatric acute lymphocytic leukemia (ALL), in which increasingly intensive combination regimens ultimately achieved high cure rates. We also describe three distinct aspects of drug independence that apply at different biological scales. The ability of these principles to quantitatively explain curative regimens suggests that supra-additive (synergistic) drug interactions are not required for successful combination therapy.

Is adding ribociclib to fulvestrant cost-effective in treating postmenopausal women with HR+/HER2- advanced or metastatic breast cancer? A US payer perspective cost utility analysis

BACKGROUND: Breast cancer is the most prevalent type of cancer in women in the United States. Ribociclib plus fulvestrant combination therapy gained US Food and Drug Administration approval to treat postmenopausal women with hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) advanced or metastatic breast cancer in 2018. OBJECTIVE: To determine the cost-effectiveness of ribociclib plus fulvestrant vs placebo plus fulvestrant therapy in the target population from a US payer perspective. METHODS: A partitioned survival analysis model composed of 3 health states (progression free, progressed disease, and death) was constructed to evaluate the cost-effectiveness of ribociclib plus fulvestrant vs placebo plus fulvestrant. The progression-free survival and the overall survival data points were extracted from published Kaplan-Meier curves in the MONALEESA-3 study and fitted to parametric curves. The safety and efficacy of the treatment was referenced from the MONALEESA-3 trial. Costs were obtained from standard sources including the Red Book for medication costs, Medicare Clinical Laboratory/Physician Fee Schedule for clinical utilization, and the literature for costs of managing adverse events, subsequent therapy, and end-of-life care. Utility and disutility values were obtained from literature to calculate quality-adjusted life-years (QALYs). One-way and probabilistic sensitivity analyses were conducted to test the model robustness. Several scenario analyses were also investigated. RESULTS: In the base case, the ribociclib plus fulvestrant arm was associated with $522,844 and 3.25 QALYs compared with $50,395 and 2.14 QALYs in the placebo plus fulvestrant arm, leading to an incremental cost-effectiveness ratio of $425,951/QALY. The cost of ribociclib had the biggest impact on the model and constituted 84% of the total cost for the ribociclib plus fulvestrant arm. The probabilistic sensitivity analysis projected that the ribociclib plus fulvestrant treatment would have a net benefit over the placebo plus fulvestrant therapy at a willingness-to-pay (WTP) threshold of $405,600/QALY. CONCLUSIONS: At a WTP threshold of $150,000/QALY, the addition of ribociclib to fulvestrant is not considered to be cost-effective in postmenopausal women with HR+/HER2- advanced or metastatic breast cancer. The findings send a strong price signal to the manufacturer and can be used to facilitate payers with price negotiation in making coverage decisions.

A meta-analysis with systematic review: Efficacy and safety of immune checkpoint inhibitors in patients with advanced gastric cancer

Background

While the efficacy of immune checkpoint inhibitors (ICIs) is increasingly recognized in advanced gastric cancer (aGC), overall survival (OS) has not been consistently improved across the different randomized controlled trials (RCTs). This meta-analysis aimed to quantify the efficacy and safety of ICI and explore potential predictive tumor tissue biomarkers in aGC.

Methods

A random-effect pairwise meta-analysis was used to evaluate the primary outcome of OS. Sensitivity analysis was performed to investigate the effects of ICIs on PD-L1 status, TMB, MSI-H, and the Asian patient population. We extracted the OS Kaplan-Meier curves from the included trials to compare the effect of PD-L1 status on response to ICIs using DigitizeIt 2.5 and Guyot's algorithm.

Results

A pairwise meta-analysis of seven RCTs included in this study showed that ICIs were more effective than the comparator in improving OS (pooled HR: 0.84). We demonstrated that PD-1 ICIs were additive when combined with the comparator arm (pooled HR: 0.79). A sensitivity analysis showed that PD-1 ICIs were associated with better OS outcomes in the Asian patient population as monotherapy (pooled HR: 0.66) or in combination with chemotherapy (pooled HR: 0.83). We demonstrated that tumors with PD-L1 ≥1 (P = 0.02) and PD-L1 ≥10 (P = 0.006) derived OS benefit from ICI monotherapy. Equally, MSI-H (P <0.00001) and TMB-high (P <0.0001) tumors derived favorable survival benefits from ICIs.

Conclusions and relevance

The results of this meta-analysis suggest that ICIs result in improved OS outcomes in aGC. The benefits varied with different ethnicities, class of ICI, PD-L1 expression, MSI status, and TMB.

Systematic Review Registration

https://www.crd.york.ac.uk/prospero, identifier (CRD42019137829).