Analyzing the pivotal trial that compared sunitinib and IFN-α in renal cell carcinoma, using a method that assesses tumor regression and growth

Depth of Radiographic Response and Time to Tumor Regrowth Predicts Overall Survival Following Anti-VEGF Therapy in Recurrent Glioblastoma

PURPOSE

Antiangiogenic therapies are known to cause high radiographic response rates due to reduction in vascular permeability resulting in a lower degree of contrast extravasation. In this study, we investigate the prognostic ability for model-derived parameters describing enhancing tumor volumetric dynamics to predict survival in recurrent glioblastoma treated with antiangiogenic therapy.

EXPERIMENTAL DESIGN

N = 276 patients in two phase II trials were used as training data, including bevacizumab ± irinotecan (NCT00345163) and cabozantinib (NCT00704288), and N = 74 patients in the bevacizumab arm of a phase III trial (NCT02511405) were used for validation. Enhancing volumes were estimated using T1 subtraction maps, and a biexponential model was used to estimate regrowth (g) and regression (d) rates, time to tumor regrowth (TTG), and the depth of response (DpR). Response characteristics were compared to diffusion MR phenotypes previously shown to predict survival.

RESULTS

Optimized thresholds occurred at g = 0.07 months-1 (phase II: HR = 0.2579, P = 5 × 10-20; phase III: HR = 0.2197, P = 5 × 10-5); d = 0.11 months-1 (HR = 0.3365, P < 0.0001; HR = 0.3675, P = 0.0113); TTG = 3.8 months (HR = 0.2702, P = 6 × 10-17; HR = 0.2061, P = 2 × 10-5); and DpR = 11.3% (HR = 0.6326, P = 0.0028; HR = 0.4785, P = 0.0206). Multivariable Cox regression controlling for age and baseline tumor volume confirmed these factors as significant predictors of survival. Patients with a favorable pretreatment diffusion MRI phenotype had a significantly longer TTG and slower regrowth.

CONCLUSIONS

Recurrent glioblastoma patients with a large, durable radiographic response to antiangiogenic agents have significantly longer survival. This information is useful for interpreting activity of antiangiogenic agents in recurrent glioblastoma.

Tumor Dynamic Model-Based Decision Support for Phase Ib/II Combination Studies: A Retrospective Assessment Based on Resampling of the Phase III Study IMpower150

PURPOSE

Model-based tumor growth inhibition (TGI) metrics are increasingly incorporated into go/no-go decisions in early clinical studies. To apply this methodology to new investigational combinations requires independent evaluation of TGI metrics in recently completed Phase III trials of effective immunotherapy.

PATIENTS AND METHODS

Data were extracted from IMpower150, a positive, randomized, Phase III study of first-line therapy in 1,202 patients with non-small cell lung cancer. We resampled baseline characteristics and longitudinal sum of longest diameters of tumor lesions of patients from both arms, atezolizumab+ bevacizumab+chemotherapy (ABCP) versus BCP, to mimic Phase Ib/II studies of 15 to 40 patients/arm with 6 to 24 weeks follow-up. TGI metrics were estimated using a bi-exponential TGI model. Effect sizes were calculated as TGI metrics geometric mean ratio (GMR), objective response rate (ORR) difference (d), and progression-free survival (PFS), hazard ratio (HR) between arms. Correct and incorrect go decisions were evaluated as the probability to achieve desired effect sizes in ABCP versus BCP and BCP versus BCP, respectively, across 500 replicated subsamples for each design.

RESULTS

For 40 patients/24 weeks follow-up, correct go decisions based on probability tumor growth rate (KG) GMR <0.90, dORR >0.10, and PFS HR <0.70 were 83%, 69%, and 58% with incorrect go decision rates of 4%, 12%, and 11%, respectively. For other designs, the ranking did not change with TGI metrics consistently overperforming RECIST endpoints. The predicted overall survival (OS) HR was around 0.80 in most of the scenarios investigated.

CONCLUSIONS

Model-based estimate of KG GMR is an exploratory endpoint that informs early clinical decisions for combination studies.

Early on-treatment tumor growth rate (EOT-TGR) determines treatment outcomes of advanced non-small-cell lung cancer patients treated with programmed cell death protein 1 axis inhibitor

BACKGROUND

Tumor growth rate (TGR), denoted as percentage change in tumor size per month, is a well-established indicator of tumor growth kinetics. The predictive value of early on-treatment TGR (EOT-TGR) for immunotherapy remains unclear. We sought to establish and validate the association of EOT-TGR with treatment outcomes in patients with advanced non-small-cell lung cancer (aNSCLC) undergoing anti-PD-1/PD-L1 (programmed cell death protein 1/programmed death-ligand 1) therapy.

PATIENTS AND METHODS

This bicenter retrospective cohort study included a training cohort, a contemporaneously treated internal validation cohort, and an external validation cohort. Computed tomography images were retrieved to calculate EOT-TGR, denoted as tumor burden change per month during a period between baseline and the first imaging evaluation after immunotherapy. Kaplan-Meier methodology and Cox regression analysis were conducted for survival analyses.

RESULTS

In the pooled cohort (n = 172), 125 patients (72.7%) were males; median age at diagnosis was 58 (range 28-79) years. Based on the training cohort, we determined the optimal cut-off value for EOT-TGR as 10.4%/month. Higher EOT-TGR was significantly associated with inferior overall survival [OS; hazard ratio (HR) 2.93, 95% confidence interval (CI) 1.47-5.83; P = 0.002], worse progression-free survival (PFS; HR 2.44, 95% CI 1.46-4.08; P = 0.001), and lower objective response rate (3.3% versus 20.9%; P = 0.040) and durable clinical benefit rate (6.7% versus 41.9%; P = 0.001). Results were reproducible in the two validation cohorts for OS and PFS. Among 43 patients who had a best response of progressive disease in the training cohort, those with high EOT-TGR had worse OS (HR 2.64; P = 0.041) and were more likely to progress due to target lesions at the first tumor evaluation (85.2% versus 0.0%; P <0.001).

CONCLUSIONS

Higher EOT-TGR was associated with inferior OS and immunotherapeutic response in patients with aNSCLC undergoing anti-PD-1/PD-L1 therapy. This easy-to-calculate radiologic biomarker may help evaluate the abilities of immunotherapy to prolong survival and assist in tailoring patients' management.

TRIAL REGISTRATION

ClinicalTrials.govNCT04722406; https://clinicaltrials.gov/ct2/show/NCT04722406.

Tumor Growth Rate Informs Treatment Efficacy in Metastatic Pancreatic Adenocarcinoma: Application of a Growth and Regression Model to Pivotal Trial and Real-World Data

BACKGROUND

Methods for screening agents earlier in development and strategies for conducting smaller randomized controlled trials (RCTs) are needed.

METHODS

We retrospectively applied a tumor growth model to estimate the rates of growth of pancreatic cancer using radiographic tumor measurements or serum CA 19-9 values from 3033 patients with stages III-IV PDAC who were enrolled in 8 clinical trials or were included in 2 large real-world data sets.

RESULTS

g correlated inversely with OS and was consistently lower in the experimental arms than in the control arms of RCTs. At the individual patient level, g was significantly faster for lesions metastatic to the liver relative to those localized to the pancreas. Regardless of regimen, g increased toward the end of therapy, often by over 3-fold.

CONCLUSIONS

Growth rates of PDAC can be determined using radiographic tumor measurement and CA 19-9 values. g is inversely associated with OS and can differentiate therapies within the same trial and across trials. g can also be used to characterize changes in the behavior of an individual's PDAC, such as differences in the growth rate of lesions based on metastatic site, and the emergence of chemoresistance. We provide examples of how g can be used to benchmark phase II and III clinical data to a virtual reference arm to inform go/no go decisions and consider novel trial designs to optimize and accelerate drug development.

Novel biomarkers in NSCLC: Radiomic analysis, kinetic analysis, and circulating tumor DNA

Current radiographic methods of measuring treatment response for patients with nonsmall cell lung cancer have significant limitations. Recently, new modalities using standard of care images or minimally invasive blood-based DNA tests have gained interest as methods of evaluating treatment response. This article highlights three emerging modalities: radiomic analysis, kinetic analysis and serum-based measurement of circulating tumor DNA, with a focus on the clinical evidence supporting these methods. Additionally, we discuss the possibility of combining these modalities to develop a robust biomarker with strong correlation to clinically meaningful outcomes that could impact clinical trial design and patient care. At Last, we focus on how these methods specifically apply to a Veteran population.

An imaging signature to predict outcome in metastatic colorectal cancer using routine computed tomography scans

BACKGROUND & AIMS

Quantitative analysis of computed tomography (CT) scans of patients with metastatic colorectal cancer (mCRC) can identify imaging signatures that predict overall survival (OS).

METHODS

We retrospectively analysed CT images from 1584 mCRC patients on two phase III trials evaluating FOLFOX ± panitumumab (n = 331, 350) and FOLFIRI ± aflibercept (n = 437, 466). In the training set (n = 720), an algorithm was trained to predict OS landmarked from month 2; the output was a signature value on a scale from 0 to 1 (most to least favourable predicted OS). In the validation set (n = 864), hazard ratios (HRs) evaluated the association of the signature with OS using RECIST1.1 as a benchmark of comparison.

RESULTS

In the training set, the selected signature combined three features - change in tumour volume, change in tumour spatial heterogeneity, and tumour volume - to predict OS. In the validation set, RECIST1.1 classified patients in three categories: response (n = 166, 19.2%), stable disease (n = 636, 73.6%), and progression (n = 62, 7.2%). The HR was 3.93 (2.79-5.54). Using the same distribution for the signature, the HR was 21.04 (14.88-30.58), showing an incremental prognostic separation. Stable disease by RECIST1.1 was reclassified by the signature along a continuum where patients belonging to the most and least favourable signature quartiles had a median OS of 40.73 (28.49 to NA) months (n = 94) and 7.03 (5.66-7.89) months (n = 166), respectively.

CONCLUSIONS

A signature combining three imaging features provides early prognostic information that can improve treatment decisions for individual patients and clinical trial analyses.

Tumor Growth Rate After Nadir Is Associated With Survival in Patients With EGFR-Mutant Non-Small-Cell Lung Cancer Treated With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor

PURPOSE

To investigate the association between tumor volume growth rate after the nadir and survival in patients with EGFR-mutant advanced non-small-cell lung cancer (NSCLC) treated with erlotinib.

MATERIALS AND METHODS

Seventy-one patients with EGFR-mutant advanced NSCLC treated with erlotinib were studied for computed tomography tumor volume kinetics during therapy. The tumor growth rate after nadir was obtained using a previously published analytic module for longitudinal volume tracking to study its relationship with overall survival (OS).

RESULTS

The median tumor volume for the cohort was 19,842 mm3 at baseline and 4,083 mm3 at nadir. The median time to nadir was 6.2 months. The tumor growth rate after nadir for logeV (the natural logarithm of tumor volume measured in mm3) was 0.11/mo on average for the cohort (SE: 0.014), which was very similar to the previously validated reference value of 0.12/mo to define slow and fast tumor growth. The OS of 48 patients with slow tumor growth (≤ 0.12/mo) was significantly longer compared with 23 patients with fast tumor growth (> 0.12/mo; median OS: 37.8 v 25.0 months; P = .0012). In Cox models, tumor growth rate was also associated with survival (regression coefficient: 3.9903; P = .0024; faster rate leads to increased hazards), after adjusting for time to nadir (regression coefficient: -0.0863; P = .0008; longer time to nadir leads to decreased hazards) and smoking history.

CONCLUSION

In patients with EGFR-mutant advanced NSCLC treated with erlotinib, slower tumor growth rates after nadir were associated with longer OS, providing a rationale for using tumor growth rates to guide precision therapy for lung cancer.

Tumor Growth Rate After Nadir Is Associated With Survival in Patients With EGFR-Mutant Non-Small-Cell Lung Cancer Treated With Epidermal Growth Factor Receptor Tyrosine Kinase Inhibitor

PURPOSE

To investigate the association between tumor volume growth rate after the nadir and survival in patients with EGFR-mutant advanced non-small-cell lung cancer (NSCLC) treated with erlotinib.

MATERIALS AND METHODS

Seventy-one patients with EGFR-mutant advanced NSCLC treated with erlotinib were studied for computed tomography tumor volume kinetics during therapy. The tumor growth rate after nadir was obtained using a previously published analytic module for longitudinal volume tracking to study its relationship with overall survival (OS).

RESULTS

The median tumor volume for the cohort was 19,842 mm³ at baseline and 4,083 mm³ at nadir. The median time to nadir was 6.2 months. The tumor growth rate after nadir for log_eV (the natural logarithm of tumor volume measured in mm³) was 0.11/mo on average for the cohort (SE: 0.014), which was very similar to the previously validated reference value of 0.12/mo to define slow and fast tumor growth. The OS of 48 patients with slow tumor growth (≤ 0.12/mo) was significantly longer compared with 23 patients with fast tumor growth (> 0.12/mo; median OS: 37.8 v 25.0 months; P = .0012). In Cox models, tumor growth rate was also associated with survival (regression coefficient: 3.9903; P = .0024; faster rate leads to increased hazards), after adjusting for time to nadir (regression coefficient: -0.0863; P = .0008; longer time to nadir leads to decreased hazards) and smoking history.

CONCLUSION

In patients with EGFR-mutant advanced NSCLC treated with erlotinib, slower tumor growth rates after nadir were associated with longer OS, providing a rationale for using tumor growth rates to guide precision therapy for lung cancer.

Tumor Growth Rate Decline despite Progressive Disease May Predict Improved Nivolumab Treatment Outcome in mRCC: When RECIST Is Not Enough

Simple Summary

The treatment scenario of metastatic renal cell carcinoma has drastically changed in recent years, with the advent of immunotherapy. Since 2015 immune-checkpoint inhibitors, either alone or in combination with other compounds, are constantly enriching the treatment scenario, with a drastic change of patients’ outcomes. The benefit from immunotherapy is difficult to capture with the currently available assessment radiological criteria. Often, with rhe use of immunotherapy, we can observe atypical patterns of response, such as hyperprogression or pseudoprogression. Pseudoprogression consists of an initial increase in tumor burden followed by a response to therapy, while hyperprogression is defined as a tumor growth rate that was at least 2-fold greater in patients with disease progression during immunotherapy. We performed a retrospective monocentric study to explore the impact of tumor growth rate change after immunotherapy administration as second or later line of treatment in patients with metastatic renal cell carcinoma.

Abstract

Treatment response is usually assessed by the response evaluation criteria in solid tumors (RECIST). These criteria may not be adequate to evaluate the response to immunotherapy, considering the peculiar patterns of response reported with this therapy. With the advent of immunotherapy these criteria have been modified to include the evaluation of the peculiar responses seen with this type of therapy (iRECIST criteria), including pseudoprogressions and hyperprogressions. Tumor growth rate (TGR) is a dynamic evaluation that takes into account the kinetics of response to treatment and may help catch the real efficacy of an immunotherapy approach. We performed a retrospective monocentric study to explore the impact of TGR change after nivolumab administration as the second or later line of treatment in patients with metastatic renal cell carcinoma (RCC). We evaluated 27 patients, divided into three categories: Disease control (DC) if there was no PD; lower velocity PD (LvPD) if disease progressed but the TGR at second assessment (TGR2) was lower than the TGR at first assessment (TGR1); higher velocity PD (HvPD) if TGR2 was higher than TGR1. The median OS for the DC group was 11.0 months (95% CI 5.0–17.0) (reference) vs. (not reached) NR (95% CI NR-NR) for LvPD (HR 0.27; 95% CI 0.06–1.30; p 0.102) vs. NR (95% CI NR–NR) for HvPD (HR 0.23; 95% CI 0.06–0.88; p 0.032). There was no difference between LvPD and DC (HR 1.21; 95% CI 0.20–7.28; p 0.838). In patients with metastatic RCC, the second or later line of nivolumab treatment may lead to a deceleration in TGR resulting in an improved survival outcome similar to that observed in patients experiencing tumor regression. In this subgroup, especially in the presence of a clinical benefit, continuing the treatment beyond progression can be recommended.

Gemcitabine plus nab-paclitaxel versus FOLFIRINOX for unresected pancreatic cancer: Comparative effectiveness and evaluation of tumor growth in Veterans

PURPOSE

Advanced, unresectable pancreatic cancer is often treated with either gemcitabine plus nab-paclitaxel (Gem/NabP) or FOLFIRINOX, although these regimens have never been compared in a head-to-head trial. In this study, we compared these two regimens using Veterans Administration (VA) data and evaluated the use of a novel tumor growth formula to predict outcomes.

METHODS

We identified 670 Veterans from national VA data with unresected stage II-IV pancreatic adenocarcinoma diagnosed between 2003 and 2016 who were treated with either first-line Gem/NabP or FOLFIRINOX. We compared overall survival (OS) and adverse events by treatment using propensity scores (PS) to account for allocation bias. Using longitudinal CA19-9 biomarker information we then fit the data to a novel tumor growth equation, comparing growth with OS.

RESULTS

We found no difference in PS-adjusted (hazard ratio [HR] 1.00; 95% confidence interval [95% CI] 0.84-1.20) or PS-matched (HR: 0.93; 95% CI: 0.76-1.13) OS between the two treatment groups. Tumor growth analysis revealed similar growth parameter values for Gem/NabP and FOLFIRINOX (P = .074 for difference).

CONCLUSIONS

Gem/NabP appeared noninferior to FOLFIRINOX for survival outcomes for advanced pancreatic adenocarcinoma based on national VA data. Biomarker-based growth equations may be useful for monitoring treatment response and predicting prognosis for pancreatic cancer.

Pre-Treatment Tumor Growth Rate Predicts Clinical Outcomes of Patients With Advanced Non-Small Cell Lung Cancer Undergoing Anti-PD-1/PD-L1 Therapy

Tumor growth rate (TGR; percent size change per month [%/m]) is postulated as an early radio-graphic predictor of response to anti-cancer treatment to overcome limitations of RECIST. We aimed to evaluate the predictive value of pre-treatment TGR (TGR₀) for outcomes of advanced non-small cell lung cancer (aNSCLC) patients treated with anti-PD-1/PD-L1 monotherapy. We retrospectively screened all aNSCLC patients who received PD-1 axis inhibitors in Sun Yat-Sen University Cancer Center between August 2016 and June 2018. TGR₀ was calculated as the percentage change in tumor size per month (%/m) derived from two computed tomography (CT) scans during a "wash-out" period before the initiation of PD-1 axis inhibition. Final follow-up date was August 28, 2019. The X-tile program was used to identify the cut-off value of TGR₀ based on maximum progression-free survival (PFS) stratification. Patients were divided into two groups per the selected TGR₀ cut-off. The primary outcome was the difference of PFS between the two groups. The Kaplan-Meier methods and Cox regression models were performed for survival analysis. A total of 80 eligible patients were included (54 [67.5%] male; median [range] age, 55 [30-74] years). Median (range) TGR₀ was 21.1 (-33.7-246.0)%/m. The optimal cut-off value of TGR₀ was 25.3%/m. Patients with high TGR₀ had shorter median PFS (1.8 months; 95% CI, 1.6 - 2.1 months) than those with low TGR₀ (2.7 months; 95% CI, 0.5 - 4.9 months) (P = 0.005). Multivariate Cox regression analysis revealed that higher TGR₀ independently predicted inferior PFS (hazard ratio [HR] 1.97; 95% CI, 1.08-3.60; P = 0.026). Higher TGR₀ was also significantly associated with less durable clinical benefit rate (34.8% vs. 8.8%, P = 0.007). High pre-treatment TGR was a reliable predictor of inferior PFS and clinical benefit in aNSCLC patients undergoing anti-PD-1/PD-L1 monotherapy. The findings highlight the role of TGR₀ as an early biomarker to predict benefit from immunotherapy and could allow tailoring patient's follow-up.

Novel Tumor Growth Rate Analysis in the Randomized CLARINET Study Establishes the Efficacy of Lanreotide Depot/Autogel 120 mg with Prolonged Administration in Indolent Neuroendocrine Tumors

Introduction

Tumor quantity while receiving cancer therapy is the sum of simultaneous regression of treatment‐sensitive and growth of treatment‐resistant fractions at constant rates. Exponential rate constants for tumor regression/decay (d) and growth (g) can be estimated. Previous studies established g as a biomarker for overall survival; g increases after treatment cessation, can estimate doubling times, and can assess treatment effectiveness in small cohorts by benchmarking to large reference data sets. Using this approach, we analyzed data from the clinical trial CLARINET, evaluating lanreotide depot/autogel 120 mg/4 weeks (LAN) for treatment of neuroendocrine tumors (NETs).

Methods and Materials

Computed tomography imaging data from 97 LAN‐ and 101 placebo‐treated patients from CLARINET were analyzed to estimate g and d.

Results

Data from 92% of LAN‐ and 94% of placebo‐treated patients could be fit to one of the equations to derive g and d (p < .001 in most data sets). LAN‐treated patients demonstrated significantly slower g than placebo recipients (p = .00315), a difference of 389 days in doubling times. No significant difference was observed in d. Over periods of LAN administration up to 700 days, g did not change appreciably. Simulated analysis with g as the endpoint showed a sample size of 48 sufficient to detect a difference in median g with 80% power.

Conclusion

Although treatment of NETs with LAN can affect tumor shrinkage, LAN primarily slows tumor growth rather than accelerates tumor regression. Evidence of LAN efficacy across tumors was identified. The growth‐retarding effect achieved with LAN was sustained for a prolonged period of time.

Implications for Practice

The only curative treatment for neuroendocrine tumors (NETs) is surgical resection; however, because of frequent late diagnosis, this is often impossible. Because of this, treatment of NETs is challenging and often aims to reduce tumor burden and delay progression. A novel method of analysis was used to examine data from the CLARINET trial, confirming lanreotide depot/autogel is effective at slowing tumor growth and extending progression‐free survival. By providing the expected rate and doubling time of tumor growth early in the course of treatment, this method of analysis has the potential to guide physicians in their management of patients with NETs.

Treatment of neuroendocrine tumors is challenging, mainly aiming to reduce tumor burden and delay disease progression. This article reports on the kinetics of tumor growth using a novel method of analysis and data from the CLARINET study.

Enhanced Detection of Treatment Effects on Metastatic Colorectal Cancer with Volumetric CT Measurements for Tumor Burden Growth Rate Evaluation

PURPOSE

Mathematical models combined with new imaging technologies could improve clinical oncology studies. To improve detection of therapeutic effect in patients with cancer, we assessed volumetric measurement of target lesions to estimate the rates of exponential tumor growth and regression as treatment is administered.

EXPERIMENTAL DESIGN

Two completed phase III trials were studied (988 patients) of aflibercept or panitumumab added to standard chemotherapy for advanced colorectal cancer. Retrospectively, radiologists performed semiautomated measurements of all metastatic lesions on CT images. Using exponential growth modeling, tumor regression (d) and growth (g) rates were estimated for each patient's unidimensional and volumetric measurements.

RESULTS

Exponential growth modeling of volumetric measurements detected different empiric mechanisms of effect for each drug: panitumumab marginally augmented the decay rate [tumor half-life; d [IQR]: 36.5 days (56.3, 29.0)] of chemotherapy [d: 44.5 days (67.2, 32.1), two-sided Wilcoxon P = 0.016], whereas aflibercept more significantly slowed the growth rate [doubling time; g = 300.8 days (154.0, 572.3)] compared with chemotherapy alone [g = 155.9 days (82.2, 347.0), P ≤ 0.0001]. An association of g with overall survival (OS) was observed. Simulating clinical trials using volumetric or unidimensional tumor measurements, fewer patients were required to detect a treatment effect using a volumetric measurement-based strategy (32-60 patients) than for unidimensional measurement-based strategies (124-184 patients).

CONCLUSIONS

Combined tumor volume measurement and estimation of tumor regression and growth rate has potential to enhance assessment of treatment effects in clinical studies of colorectal cancer that would not be achieved with conventional, RECIST-based unidimensional measurements.

Efficacy and Prognostic Factors of Sunitinib as First-Line Therapy for Patients With Metastatic Renal Cell Carcinoma in an Arab Population

PURPOSE

Antiangiogenic tyrosine kinase inhibitors have been the mainstay first-line therapy for metastatic renal cell carcinoma (mRCC). We reviewed the efficacy of first-line therapy with sunitinib in patients with mRCC in an Arab population.

METHODS

Medical records of patients with mRCC treated at a tertiary care center in Saudi Arabia, during the period from 2007 to 2016, were reviewed. Demographic data, treatment received, response, and prognostic factors were analyzed.

RESULTS

Fifty-five patients who received sunitinib were identified. The median age was 60 years (range, 18 to 78 years), and 42 of the 55 patients were men (76.3%). International Metastatic RCC Diagnostic Consortium prognostic scores for favorable/intermediate/poor were 14.5%/43.6%/38.2%, respectively. The median performance status was 1, and the median Charlson comorbidity index score was 9. Thirty-seven patients (67.2%) had cytoreductive nephrectomy. Thirty-seven patients (67.2%) had clear cell histology. Twenty-two patients (40%) underwent dose reduction. Twenty-seven patients (49%) received second-line therapy, and seven patients (12.7%) received third-line therapy. Response rates were complete response in one patient (1.8%), partial response in 17 (30.9%), stable disease in 10 (18.1), and disease progression in 20 (36.3%). Progression-free survival (PFS) and overall survival (OS) were 6.0 and 24.7 months, respectively. Univariate analysis showed statistically improved PFS for dose reduction (P = .015) and the development of hypothyroidism (P = .03). It also showed statistically improved OS for dose reduction (P = .035), hypothyroidism (P = .0002), and cytoreductive nephrectomy (P = .0052). Multivariate analysis showed statistically improved PFS for dose reduction (P = .01) and OS for development of hypothyroidism (P = .007).

CONCLUSION

Our data for sunitinib in mRCC show significantly lower PFS than expected. The absence of prognostic value of the International Metastatic RCC Diagnostic Consortium scoring system and pathologic subtype warrant further investigation and possible inclusion of genetic scoring in this ethnic group of patients.

Tumour growth rate as a tool for response evaluation during PD-1 treatment for non-small cell lung cancer: a retrospective analysis

Background

Immune checkpoint inhibitors have emerged as a standard of care treatment for non-small cell lung cancer (NSCLC). To get insight into variations in tumour growth kinetics and their potential predictive values for outcome, we evaluated tumour growth rate (TGR) in patients receiving programmed cell death 1 (PD-1) checkpoint inhibitors.

Patients and methods

Differences in TGR before and after the start of treatment were calculated by entering the sum of the longest diameters from computer tomography scans before and after the initiation of therapy into a formula that assumes volumetric exponential tumour growth. TGR variations, possible predictors for TGR changes and its relationship to overall survival (OS) were studied. For comparison, tumour response was assessed using Response Evaluation Criteria in Solid Tumours (RECIST) version 1.1.

Results

Among the 58 evaluable patients, 37 patients (64%) showed deceleration of TGR and 16 patients (27%) showed an acceleration of TGR after initiation of therapy, with a significant difference in median OS of 18.0 months versus 6.0 months (hazard ratio 0.35, 95% CI 0.18–0.71) between these groups. Four patients (7%) were defined as having hyperprogressive disease. In five patients (9%), tumour growth remained stable. These TGR categories were not significantly different according to age, sex, histology, smoking or previous radiotherapy. Of the patients defined as having progressive disease by RECIST version 1.1 at first follow-up, 40% showed response to checkpoint inhibitors by a decrease in TGR.

Conclusion

Tumour growth kinetics can be used as a clinically relevant predictor for OS in anti-PD-1-treated patients with NSCLC, and may provide additional information to RECIST measurements.

Tumour growth rate changes can be used as a clinically relevant predictor of overall survival during PD-1 inhibitor therapy for NSCLC and provide additional information to RECIST measurements alonehttp://bit.ly/2nxT17e

Vol-PACT: A Foundation for the NIH Public-Private Partnership That Supports Sharing of Clinical Trial Data for the Development of Improved Imaging Biomarkers in Oncology

PURPOSE

To develop a public-private partnership to study the feasibility of a new approach in collecting and analyzing clinically annotated imaging data from landmark phase III trials in advanced solid tumors.

PATIENTS AND METHODS

The collection of clinical trials fulfilled the following inclusion criteria: completed randomized trials of > 300 patients, highly measurable solid tumors (non-small-cell lung cancer, colorectal cancer, renal cell cancer, and melanoma), and required sponsor and institutional review board sign-offs. The new approach in analyzing computed tomography scans was to transfer to an academic image analysis laboratory, draw contours semi-automatically by using in-house-developed algorithms integrated into the open source imaging platform Weasis, and perform serial volumetric measurement.

RESULTS

The median duration of contracting with five sponsors was 12 months. Ten trials in 7,085 patients that covered 12 treatment regimens across 20 trial arms were collected. To date, four trials in 3,954 patients were analyzed. Source imaging data were transferred to the academic core from 97% of trial patients (n = 3,837). Tumor imaging measurements were extracted from 82% of transferred computed tomography scans (n = 3,162). Causes of extraction failure were nonmeasurable disease (n = 392), single imaging time point (n = 224), and secondary captured images (n = 59). Overall, clinically annotated imaging data were extracted in 79% of patients (n = 3,055), and the primary trial end point analysis in each trial remained representative of each original trial end point.

CONCLUSION

The sharing and analysis of source imaging data from large randomized trials is feasible and offer a rich and reusable, but largely untapped, resource for future research on novel trial-level response and progression imaging metrics.

Tumor growth rate as a metric of progression, response, and prognosis in pancreatic and intestinal neuroendocrine tumors

Background

Lanreotide depot/autogel antitumor activity in intestinal/pancreatic neuroendocrine tumors (NETs) was demonstrated in the phase-3 CLARINET study (NCT00353496), based on significantly prolonged progression-free survival (PFS) versus placebo.

Methods

During CLARINET, patients with metastatic intestinal/pancreatic NETs received lanreotide depot/autogel 120 mg or placebo every 4 weeks for 96 weeks. Imaging data (response evaluation criteria in solid tumors [RECIST] v1.0, centrally reviewed) were re-evaluated in this post hoc analysis of tumor growth rate (TGR) in NETs. TGR (%/month) was calculated from two imaging scans during relevant periods: pre-treatment (TGR₀); 12–24 weeks before randomization versus baseline; each treatment visit versus baseline (TGR_Tx-0); between consecutive treatment visits (TGR_Tx-Tx). To assess TGR as a measure of prognosis, PFS was compared for TGR₀ subgroups stratified by optimum TGR₀ cut-off; a multivariate analysis was conducted to identify prognostic factors for PFS.

Results

TGR₀ revealed tumors growing during pre-treatment (median [interquartile range] TGR₀: lanreotide 2.1%/month [0.2; 6.1]; placebo 2.7%/month [0.15; 6.8]), contrary to RECIST status. TGR was significantly reduced by 12 weeks with lanreotide versus placebo (difference in least-square mean TGR_0–12 of − 2.9 [− 5.1, − 0.8], p = 0.008), a difference that was maintained at most subsequent visits. TGR₀ > 4%/month had greater risk of progression/death than ≤4%/month (hazard ratio 4.1; [95% CI 2.5–6.5]; p < 0.001); multivariate analysis revealed lanreotide treatment, progression at baseline, TGR₀, hepatic tumor load, and primary tumor type were independently associated with PFS.

Conclusions

TGR provides valuable information on tumor activity and prognosis in patients with metastatic intestinal/pancreatic NETs, and identifies early lanreotide depot/autogel antitumor activity.

Trial registration

Retrospective registration, 18 July 2006; EudraCT: 2005–004904-35; ClinicalTrials.gov: NCT00353496.

Electronic supplementary material

The online version of this article (10.1186/s12885-018-5257-x) contains supplementary material, which is available to authorized users.

Tumor Response Assessment for Precision Cancer Therapy: Response Evaluation Criteria in Solid Tumors and Beyond

Objective assessment of tumor responses and treatment results has been the basis for the advancement of cancer therapies, and imaging plays a key role to provide a "common language" to describe the results of cancer treatment. Although Response Evaluation Criteria in Solid Tumors (RECIST) has been the most widely accepted method for assessing tumor response in the past decades, the limitations of RECIST have increasingly becoming recognized, especially with the recent advances of precision-medicine approaches to cancer. This article reviews the current concept of tumor response evaluations based on RECIST, describes the limitations of RECIST, and proposes strategies to overcome the limitations. The article emphasizes specific limitations in the setting of precision cancer therapy and cancer immunotherapy and discusses the important insights provided by the cutting-edge investigations in the emerging fields.

Automated image analysis tool for tumor volume growth rate to guide precision cancer therapy: EGFR-mutant non-small-cell lung cancer as a paradigm

PURPOSE

To develop an automated analytic module for calculation of tumor growth rate from serial CT scans and to apply the module and evaluate reproducibility in a pilot cohort of advanced NSCLC patients with EGFR mutations treated with EGFR tyrosine kinase inhibitors.

MATERIALS AND METHODS

The module utilized a commercially available image-processing workstation equipped with a validated tumor volume measurement tool. An automated analytic software module was programmed with the capability to record and display serial tumor volume changes and to calculate tumor volume growth rate over time and added to the workstation. The module was applied to evaluate the tumor growth rate in a pilot cohort of 24 EGFR-mutant patients treated with EGFR inhibitors, and reproducibility references as tested by two independent thoracic radiologists.

RESULTS

The module analyzed chest CT scans from 24 patients (5 males, 19 females; median age: 61) with a median of 8 scans per patient, totaling 227 scans and provided a graphical display with an automated and instant calculation of tumor growth rate after the nadir volume for each patient. High inter and intraobserver agreements were noted for tumor growth rates, with concordance correlation coefficients of 0.9323 and 0.9668, respectively. Interpretation of slow versus fast tumor growth using previously identified threshold of ≤0.15/month had a perfect interobserver agreement (κ = 1.00), and an excellent intraobserver agreement (κ = 0.895).

CONCLUSIONS

The present study describes the development of an image analytic module for assessing tumor growth rate and the data demonstrates the functionality and reproducibility of the module in a pilot cohort of EGFR-mutant NSCLC patients treated with EGFR-TKI. The image analytic module is an initial step for clinical translation of the tumor growth rate approach to guide cancer treatment in precision oncology.

On the relationship between tumour growth rate and survival in non-small cell lung cancer

A recurrent question within oncology drug development is predicting phase III outcome for a new treatment using early clinical data. One approach to tackle this problem has been to derive metrics from mathematical models that describe tumour size dynamics termed re-growth rate and time to tumour re-growth. They have shown to be strong predictors of overall survival in numerous studies but there is debate about how these metrics are derived and if they are more predictive than empirical end-points. This work explores the issues raised in using model-derived metric as predictors for survival analyses. Re-growth rate and time to tumour re-growth were calculated for three large clinical studies by forward and reverse alignment. The latter involves re-aligning patients to their time of progression. Hence, it accounts for the time taken to estimate re-growth rate and time to tumour re-growth but also assesses if these predictors correlate to survival from the time of progression. I found that neither re-growth rate nor time to tumour re-growth correlated to survival using reverse alignment. This suggests that the dynamics of tumours up until disease progression has no relationship to survival post progression. For prediction of a phase III trial I found the metrics performed no better than empirical end-points. These results highlight that care must be taken when relating dynamics of tumour imaging to survival and that bench-marking new approaches to existing ones is essential.

Neutral evolution of drug resistant colorectal cancer cell populations is independent of their KRAS status

Emergence of tumor resistance to an anti-cancer therapy directed against a putative target raises several questions including: (1) do mutations in the target/pathway confer resistance? (2) Are these mutations pre-existing? (3) What is the relative fitness of cells with/without the mutation? We addressed these questions in patients with metastatic colorectal cancer (mCRC). We conducted an exhaustive review of published data to establish a median doubling time for CRCs and stained a cohort of CRCs to document mitotic indices. We analyzed published data and our own data to calculate rates of growth (g) and regression (d, decay) of tumors in patients with CRC correlating these results with the detection of circulating MT-KRAS DNA. Additionally we estimated mathematically the caloric burden of such tumors using data on mitotic and apoptotic indices. We conclude outgrowth of cells harboring intrinsic or acquired MT-KRAS cannot explain resistance to anti-EGFR (epidermal growth factor receptor) antibodies. Rates of tumor growth with panitumumab are unaffected by presence/absence of MT-KRAS. While MT-KRAS cells may be resistant to anti-EGFR antibodies, WT-KRAS cells also rapidly bypass this blockade suggesting inherent resistance mechanisms are responsible and a neutral evolution model is most appropriate. Using the above clinical data on tumor doubling times and mitotic and apoptotic indices we estimated the caloric intake required to support tumor growth and suggest it may explain in part cancer-associated cachexia.

A Phase II Study of Dovitinib in Patients with Recurrent or Metastatic Adenoid Cystic Carcinoma

Purpose: Genetic and preclinical studies have implicated FGFR signaling in the pathogenesis of adenoid cystic carcinoma (ACC). Dovitinib, a suppressor of FGFR activity, may be active in ACC.Experimental Design: In a two-stage phase II study, 35 patients with progressive ACC were treated with dovitinib 500 mg orally for 5 of 7 days continuously. The primary endpoints were objective response rate and change in tumor growth rate. Progression-free survival, overall survival, metabolic response, biomarker, and quality of life were secondary endpoints.Results: Of 34 evaluable patients, 2 (6%) had a partial response and 22 (65%) had stable disease >4 months. Median PFS was 8.2 months and OS was 20.6 months. The slope of the overall TGR fell from 1.95 to 0.63 on treatment (P < 0.001). Toxicity was moderate; 63% of patients developed grade 3-4 toxicity, 94% required dose modifications, and 21% stopped treatment early. An early metabolic response based on 18FDG-PET scans was seen in 3 of 15 patients but did not correlate with RECIST response. MYB gene translocation was observed and significantly correlated with overexpression of MYB but did not correlate with FGFR1 phosphorylation or clinical response to dovitinib.Conclusions: Dovitinib produced few objective responses in patients with ACC but did suppress the TGR with a PFS that compares favorably with those reported with other targeted agents. Future studies of more potent and selective FGFR inhibitors in biomarker-selected patients will be required to determine whether FGFR signaling is a valid therapeutic target in ACC. Clin Cancer Res; 23(15); 4138-45. ©2017 AACR.

Romidepsin is effective and well tolerated in older patients with peripheral T-cell lymphoma: analysis of two phase II trials

Peripheral T-cell lymphomas (PTCLs) are a rare group of lymphoid neoplasms with high relapse rates after initial therapy and poor prognosis. Most patients are aged ≥60 years and are often not candidates for aggressive salvage therapies. Romidepsin, a potent class I histone deacetylase inhibitor, has shown significant single-agent activity in relapsed/refractory PTCL. We evaluated the efficacy and tolerability of romidepsin in elderly patients in this setting. Ninety-five patients aged ≥60 years were identified from 2 prospective phase 2 registration trials of romidepsin, and comparative analyses were performed with younger patients from these trials. Response rates, progression-free survival, and overall survival were not statistically different for younger vs older patients. The toxicity profile in older and younger patients was similar in both trials. Romidepsin demonstrated similar efficacy and tolerability in younger and older patients and presents an attractive treatment option for relapsed/refractory PTCL regardless of age.

TRIAL REGISTRATION

Clinicaltrials.gov identifiers: NCT00426764, NCT00007345.

Sunitinib: Ten Years of Successful Clinical Use and Study in Advanced Renal Cell Carcinoma

The oral multikinase inhibitor sunitinib malate was approved by the U.S. Food and Drug Administration in January 2006 for use in patients with advanced renal cell carcinoma (RCC). Since then, it has been approved globally for this indication and for patients with imatinib-resistant or -intolerant gastrointestinal stromal tumors and advanced pancreatic neuroendocrine tumors. As we mark the 10-year anniversary of the beginning of the era of targeted therapy, and specifically the approval of sunitinib, it is worthwhile to highlight the progress that has been made in advanced RCC as it relates to the study of sunitinib. We present the key trials and data for sunitinib that established it as a reference standard of care for first-line advanced RCC therapy and, along with other targeted agents, significantly altered the treatment landscape in RCC. Moreover, we discuss the research with sunitinib that has sought to refine its role via patient selection and prognostic markers, improve dosing and adverse event management, and identify predictive efficacy biomarkers, plus the extent to which this research has contributed to the overall understanding and management of RCC. We also explore the key learnings regarding study design and data interpretation from the sunitinib studies and how these findings and the sunitinib development program, in general, can be a model for successful development of other agents. Finally, ongoing research into the continued and future role of sunitinib in RCC management is discussed.

THE ONCOLOGIST

2017;22:41-52 IMPLICATIONS FOR PRACTICE: Approved globally, sunitinib is established as a standard of care for first-line advanced renal cell carcinoma (RCC) therapy and, along with other targeted agents, has significantly altered the treatment landscape in RCC. Research with sunitinib that has sought to refine its role via patient selection and prognostic markers, improve dosing and adverse event management, and identify predictive efficacy biomarkers has contributed to the overall understanding and management of RCC. Key learnings regarding study design and data interpretation from the sunitinib studies and the sunitinib development program, in general, can be a model for the successful development of other agents.

Optimizing clinical benefit with targeted treatment in mRCC: "Tumor growth rate" as an alternative clinical endpoint

Tumor growth rate (TGR), usually defined as the ratio between the slope of tumor growth before the initiation of treatment and the slope of tumor growth during treatment, between the nadir and disease progression, is a measure of the rate at which tumor volume increases over time. In patients with metastatic renal cell carcinoma (mRCC), TGR has emerged as a reliable alternative parameter to allow a quantitative and dynamic evaluation of tumor response. This review presents evidence on the correlation between TGR and treatment outcomes and discusses the potential role of this tool within the treatment scenario of mRCC. Current evidence, albeit of retrospective nature, suggests that TGR might represent a useful tool to assess whether treatment is altering the course of the disease, and has shown to be significantly associated with progression-free survival and overall survival. Therefore, TGR may represent a valuable endpoint for clinical trials evaluating new molecularly targeted therapies. Most importantly, incorporation of TGR in the assessment of individual patients undergoing targeted therapies may help clinicians decide if a given agent is no longer able to control disease growth and whether continuing therapy beyond RECIST progression may still produce clinical benefit.

Predicting survival of pancreatic cancer patients treated with gemcitabine using longitudinal tumour size data

Purpose

Measures derived from longitudinal tumour size data have been increasingly utilised to predict survival of patients with solid tumours. The aim of this study was to examine the prognostic value of such measures for patients with metastatic pancreatic cancer undergoing gemcitabine therapy.

Methods

The control data from two Phase III studies were retrospectively used to develop (271 patients) and validate (398 patients) survival models. Firstly, 31 baseline variables were screened from the training set using penalised Cox regression. Secondly, tumour shrinkage metrics were interpolated for each patient by hierarchical modelling of the tumour size time-series. Subsequently, survival models were built by applying two approaches: the first aimed at incorporating model-derived tumour size metrics in a parametric model, and the second simply aimed at identifying empirical factors using Cox regression. Finally, the performance of the models in predicting patient survival was evaluated on the validation set.

Results

Depending on the modelling approach applied, albumin, body surface area, neutrophil, baseline tumour size and tumour shrinkage measures were identified as potential prognostic factors. The distributional assumption on survival times appeared to affect the identification of risk factors but not the ability to describe the training data. The two survival modelling approaches performed similarly in predicting the validation data.

Conclusions

A parametric model that incorporates model-derived tumour shrinkage metrics in addition to other baseline variables could predict reasonably well survival of patients with metastatic pancreatic cancer. However, the predictive performance was not significantly better than a simple Cox model that incorporates only baseline characteristics.

Electronic supplementary material

The online version of this article (doi:10.1007/s00280-016-2994-x) contains supplementary material, which is available to authorized users.

Volumetric Tumor Response and Progression in EGFR-mutant NSCLC Patients Treated with Erlotinib or Gefitinib

RATIONALE AND OBJECTIVES

The aims of this study were to investigate the association between 8-week tumor volume decrease and survival in an independent cohort of epidermal growth factor receptor (EGFR)-mutant advanced non-small cell lung cancer (NSCLC) patients treated with first-line erlotinib or gefitinib, and to assess the rate of their volumetric tumor growth after the volume nadir.

MATERIALS AND METHODS

In patients with advanced NSCLC harboring sensitizing EGFR mutations treated with first-line erlotinib or gefitinib, computed tomography (CT) tumor volumes of dominant lung lesions were analyzed for (1) the association with survival, and (2) the volumetric tumor growth rate after the volume nadir.

RESULTS

In 44 patients with the 8-week follow-up CT, the 8-week tumor volume decrease (%) was significantly associated with longer overall survival when fitted as a continuous variable in a Cox model (P = 0.01). The growth rate of the logarithm of tumor volume (logeV), obtained using a linear mixed-effects model adjusting for time since baseline, was 0.096/month (SE: 0.013/month; 95% confidence interval [CI]: 0.071-0.12/month), which was similar to the rate of 0.12/month (SE: 0.015/month; 95%CI: 0.090-0.15/month) observed in the previous report.

CONCLUSIONS

The 8-week tumor volume decrease was validated as a marker for longer survival in the independent cohort of EGFR-mutant NSCLC patients treated with first-line erlotinib or gefitinib. The volumetric tumor growth rate after the nadir in this cohort was similar to that of the previous cohort, indicating the reproducibility of the observation among different patient cohorts.

Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling

Quantitative assessments of tumor burden and modeling of longitudinal growth could improve phase II oncology trials. To identify obstacles to wider use of quantitative measures we obtained recorded linear tumor measurements from three published lung cancer trials. Model-based parameters of tumor burden change were estimated and compared with similarly sized samples from separate trials. Time-to-tumor growth (TTG) was computed from measurements recorded on case report forms and a second radiologist blinded to the form data. Response Evaluation Criteria in Solid Tumors (RECIST)-based progression-free survival (PFS) measures were perfectly concordant between the original forms data and the blinded radiologist re-evaluation (intraclass correlation coefficient = 1), but these routine interrater differences in the identification and measurement of target lesions were associated with an average 18-week delay (range, -20 to 55 weeks) in TTG (intraclass correlation coefficient = 0.32). To exploit computational metrics for improving statistical power in small clinical trials will require increased precision of tumor burden assessments.

A case study on the potential angiogenic effect of human chorionic gonadotropin hormone in rapid progression and spontaneous regression of metastatic renal cell carcinoma during pregnancy and after surgical abortion

BACKGROUND

Treatment possibilities of metastatic renal cell carcinoma (mRCC) have recently changed dramatically prolonging the overall survival of the patients. This kind of development brings new challenges for the care of mRCC.

CASE PRESENTATION

A 22 year-old female patient with translocation type mRCC, who previously had been treated for nearly 5 years, became pregnant during the treatment break period. Follow-up examinations revealed a dramatic clinical and radiological progression of mRCC in a few weeks therefore the pregnancy was terminated. A few days after surgical abortion, CT examination showed a significant spontaneous regression of the pulmonary metastases, and the volume of the largest manifestation decreased from ca. 30 to 3.5 cm(3) in a week. To understand the possible mechanism of this spectacular regression, estrogen, progesterone and luteinizing hormone receptors (ER, PGR and LHR, respectively) immuno-histochemistry assays were performed on the original surgery samples. Immuno-histochemistry showed negative ER, PGR and positive LHR status suggesting the possible angiogenic effect of human chorionic gonadotropin hormone (hCG) in the background.

CONCLUSION

We hypothesize that pregnancy may play a causal role in the progression of mRCC via the excess amount of hCG, however, more data are necessary to validate the present notions and the predictive role of LHR overexpression.

Therapies with diverse mechanisms of action kill cells by a similar exponential process in advanced cancers

Successful cancer treatments are generally defined as those that decrease tumor quantity. In many cases, this decrease occurs exponentially, with deviations from a strict exponential being attributed to a growing fraction of drug-resistant cells. Deviations from an exponential decrease in tumor quantity can also be expected if drugs have a nonuniform spatial distribution inside the tumor, for example, because of interstitial pressure inside the tumor. Here, we examine theoretically different models of cell killing and analyze data from clinical trials based on these models. We show that the best description of clinical outcomes is by first-order kinetics with exponential decrease of tumor quantity. We analyzed the total tumor quantity in a diverse group of clinical trials with various cancers during the administration of different classes of anticancer agents and in all cases observed that the models that best fit the data describe the decrease of the sensitive tumor fraction exponentially. The exponential decrease suggests that all drug-sensitive cancer cells have a single rate-limiting step on the path to cell death. If there are intermediate steps in the path to cell death, they are not rate limiting in the observational time scale utilized in clinical trials--tumor restaging at 6- to 8-week intervals. On shorter time scales, there might be intermediate steps, but the rate-limiting step is the same. Our analysis, thus, points to a common pathway to cell death for cancer cells in patients. See all articles in this Cancer Research section, "Physics in Cancer Research."

Optimizing oncology therapeutics through quantitative translational and clinical pharmacology: challenges and opportunities

Despite advances in biomedical research that have deepened our understanding of cancer hallmarks, resulting in the discovery and development of targeted therapies, the success rates of oncology drug development remain low. Opportunities remain for objective dose selection informed by exposure-response understanding to optimize the benefit-risk balance of novel therapies for cancer patients. This review article discusses the principles and applications of modeling and simulation approaches across the lifecycle of development of oncology therapeutics. Illustrative examples are used to convey the value gained from integration of quantitative clinical pharmacology strategies from the preclinical-translational phase through confirmatory clinical evaluation of efficacy and safety.

Evidence and Clinical Relevance of Tumor Flare in Patients Who Discontinue Tyrosine Kinase Inhibitors for Treatment of Metastatic Renal Cell Carcinoma

BACKGROUND

Several tyrosine kinase inhibitors (TKIs) and one monoclonal antibody targeting the vascular endothelial growth factor (VEGF)/VEGF receptor (VEGFR) axis have been approved for the treatment of metastatic renal cell carcinoma (mRCC). Preclinical data suggest that cessation of anti-VEGF therapy may generate a tumor flare (TF) but its clinical relevance is still questionable.

OBJECTIVE

This analysis investigates the occurrence of tumor flare and its prognostic role after discontinuation of anti-VEGFR TKIs in patients affected by mRCC.

DESIGN, SETTING, AND PARTICIPANTS

Patients with mRCC treated with first-line sunitinib or pazopanib at standard dosages were screened. Patients included in the analysis were required to have: (1) discontinued treatment because of progression of disease or intolerable toxicity or sustained response; (2) evaluation of tumor growth rates immediately before (GR1) and after discontinuation (GR2); and (3) no treatment during evaluation of GR2.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Overall survival (OS) was the main outcome. TF was calculated as the difference between the GR values (TF=GR2 - GR1). Cox proportional hazards regression was used to assess the prognostic role.

RESULTS AND LIMITATIONS

Sixty-three consecutive patients were analyzed; the median duration of treatment was 9.3 mo, the median progression-free survival (PFS) was 11.1 mo, and the median OS was 41.5 mo. The reasons for treatment discontinuation were sustained response (partial response/stable disease) in 15.9%, toxicity in 22.2%, and progression of disease in 61.9% of cases. The median GR1 and GR2 were 0.16cm/mo (interquartile range [IQR] -0.07 to 0.53) and 0.70cm/mo (IQR 0.21-1.46), respectively (p=0.001). In the overall population, the median TF was 0.55cm/mo (IQR 0.08-1.22) and differed according to the reason for discontinuation: 0.15cm/mo for response, 0.95cm/mo for toxicity, and 1.66cm/mo for progression. When TF was compared to other prognostic variables, Cox analysis confirmed its prognostic role (hazard ratio 1.11, 95% confidence interval 1.001-1.225; p=0.048).

CONCLUSIONS

This study reports clinical evidence that TKI discontinuation results in acceleration of tumor GR and induces TF, which can negatively affect the prognosis of mRCC patients.

PATIENT SUMMARY

In this report, we looked at the outcomes for patients affected by metastatic kidney tumors who discontinued treatment with antiangiogenic agents. We found that tumor regrowth after discontinuation of therapy was related to the reason for discontinuation: regrowth was higher in patients who discontinued treatment because of disease progression, and lower in patients who discontinued treatment because of a sustained response. Moreover, we found that the higher the growth rate, the shorter the survival. We conclude that discontinuation of antiangiogenic agents may cause an increase in tumor growth rate, which is related to patient survival.

Continuing a cancer treatment despite tumor growth may be valuable: sunitinib in renal cell carcinoma as example

BACKGROUND

The US FDA and the EMA have approved seven agents for the treatment of renal cell carcinoma, primarily based on differences in progression-free survival (PFS). Because PFS is an arbitrary endpoint we hypothesized that an analysis would demonstrate the growth rate of tumors remained constant at the time of RECIST-defined disease progression.

METHODS

We previously estimated the growth (g) and regression (d) rates and the stability of g using data from the Phase III trial comparing sunitinib and interferon.

RESULTS

Sufficient data were available and rate constants statistically valid in 321 of 374 patients randomized to sunitinib. Median d was 0•0052 days(-1); in 53 patients no tumor growth was recorded. Median g was 0•00082 days(-1) and was stable for a median of 275 days on therapy, remaining stable beyond 300, 600 and 900 days in 122, 65 and 27 patients, respectively. A possible increase in g while receiving sunitinib could be discerned in only 18 of 321 patients. Given a median g of 0•00082 days(-1) the estimated median time to a second progression were sunitinib continued past RECIST-defined progression was 7.3 months. At 100, 200, and 300 days after starting therapy, an estimated 47%, 27%, and 13% of tumor remains sunitinib sensitive and could explain a RECIST-defined response to a new TKI.

CONCLUSION

Prolonged stability of g with sunitinib suggests continued sunitinib beyond RECIST-defined progression may provide a beneficial outcome. Randomized trials in patients whose disease has "progressed" on sunitinib are needed to test this hypothesis.

The VEGF inhibitor axitinib has limited effectiveness as a therapy for adrenocortical cancer

CONTEXT

Adrenocortical carcinoma (ACC) is a rare malignancy with a poor prognosis in need of more effective treatment options. Published evidence indicates many ACCs express the vascular endothelial growth factor receptor (VEGFR), suggesting inhibiting vascular endothelial growth factor signaling could potentially impact tumor growth.

OBJECTIVE

The objective of the study was to determine the antitumor efficacy of axitinib (AG-013736), a potent, selective inhibitor of VEGFR1, -2, and -3.

DESIGN

This was a phase II, open-label trial using a two-stage design.

PATIENTS

Thirteen patients with metastatic ACC previously treated with at least one chemotherapy regimen with or without mitotane participated in the study.

INTERVENTION

Starting axitinib dose was 5 mg orally twice daily. Dose escalations were permitted if the administered dose was tolerable.

RESULTS

Thirteen patients were enrolled. Dose escalation was possible in seven patients, but the majority could not tolerate a dose higher than the starting 5 mg, twice-daily dose for prolonged periods of time. All patients experienced known grade 1/2 toxicities, and 10 of 13 patients had at least one grade 3/4 adverse event. No patient tumor could be scored as a Response Evaluation Criteria in Solid Tumors response, although the growth rate on therapy compared with that prior to starting axitinib was reduced in 4 of the 13 patients. The median progression-free survival was 5.48 months, and the median overall survival was longer than 13.7 months.

CONCLUSION

Axitinib has limited effectiveness in ACC. Together with 48 patients previously reported who received either sorafenib or sunitinib, a total of 61 ACC patients have now been treated with a VEGFR tyrosine kinase inhibitor without an objective Response Evaluation Criteria in Solid Tumors response. Future trials in ACC should look to other targets for possible active agents.

Simplifying the complexity of resistance heterogeneity in metastasis

The main goal of treatment regimens for metastasis is to control growth rates, not eradicate all cancer cells. Mathematical models offer methodologies that incorporate high-throughput data with dynamic effects on net growth. The ideal approach would simplify, but not over-simplify, a complex problem into meaningful and manageable estimators that predict the response of a patient to specific treatments. We explore here three fundamental approaches with different assumptions concerning resistance mechanisms in which the cells are categorized into either discrete compartments or described by a continuous range of resistance levels. We argue in favor of modeling resistance as a continuum, and demonstrate how integrating cellular growth rates, density-dependent versus exponential growth, and intratumoral heterogeneity improves predictions concerning the resistance heterogeneity of metastases.

Tumor growth rate is an early indicator of antitumor drug activity in phase I clinical trials

PURPOSE

Response Evaluation Criteria in Solid Tumors (RECIST) evaluation does not take into account the pretreatment tumor kinetics and may provide incomplete information about experimental drug activity. Tumor growth rate (TGR) allows for a dynamic and quantitative assessment of the tumor kinetics. How TGR varies along the introduction of experimental therapeutics and is associated with outcome in phase I patients remains unknown.

EXPERIMENTAL DESIGN

Medical records from all patients (N = 253) prospectively treated in 20 phase I trials were analyzed. TGR was computed during the pretreatment period (reference) and the experimental period. Associations between TGR, standard prognostic scores [Royal Marsden Hospital (RMH) score], and outcome [progression-free survival (PFS) and overall survival (OS)] were computed (multivariate analysis).

RESULTS

We observed a reduction of TGR between the reference versus experimental periods (38% vs. 4.4%; P < 0.00001). Although most patients were classified as stable disease (65%) or progressive disease (25%) by RECIST at the first evaluation, 82% and 65% of them exhibited a decrease in TGR, respectively. In a multivariate analysis, only the decrease of TGR was associated with PFS (P = 0.004), whereas the RMH score was the only variable associated with OS (P = 0.0008). Only the investigated regimens delivered were associated with a decrease of TGR (P < 0.00001, multivariate analysis). Computing TGR profiles across different clinical trials reveals specific patterns of antitumor activity.

CONCLUSIONS

Exploring TGR in phase I patients is simple and provides clinically relevant information: (i) an early and subtle assessment of signs of antitumor activity; (ii) independent association with PFS; and (iii) it reveals drug-specific profiles, suggesting potential utility for guiding the further development of the investigational drugs.

Changing T-cell enigma: cancer killing or cancer control?

Data from different laboratories and theoretical considerations challenge our current view on anticancer immunity. Immune cells are capable of destroying cancer cells under in vitro and in vivo conditions. Therefore, cellular immunity is considered to control cancers through mechanisms that kill cancers. Yet, therapeutic anticancer immune responses rarely delete cancers. If efficient, they rather establish a life with stable disease. This raises the question of whether killing is the sole mechanism by which immune therapy attacks cancers. Here, we show that, besides cancer eradication by cytotoxic lymphocytes, other modes of action are operative and strictly required for cancer control. We show that T helper-1 cells arrest cancer growth by driving cancers into a state of stable or permanent growth arrest, called senescence. Such immune cells establish cytokine-producing walls around developing cancers. When producing interferon-γ and tumor necrosis factor, this cytokine-induced tumor immune-surveillance keeps the cancer cells in a permanently non-proliferating state. Simultaneously, antiangiogenic chemokines cut their connections to the surrounding tissues. This strategy significantly reduces tumor burden and prolongs life of cancer-bearing animals. As human cancers also undergo senescence, the current data suggest tumor-immune surveillance through cytokine-induced senescence, instead of tumor eradication, as the more realistic and primary goal of cancer control.

Tumor growth rate provides useful information to evaluate sorafenib and everolimus treatment in metastatic renal cell carcinoma patients: an integrated analysis of the TARGET and RECORD phase 3 trial data

BACKGROUND

Response Evaluation Criteria in Solid Tumors (RECIST) criteria may not be sufficient to evaluate the response of targeted therapies in metastatic renal cell carcinoma (mRCC). The tumor growth rate (TGR) incorporates the time between evaluations and may be adequate.

OBJECTIVE

To determine how TGR is modified along the treatment sequence and is associated with outcome in mRCC patients.

DESIGN, SETTING, AND PARTICIPANTS

Medical records from all patients prospectively treated at Gustave Roussy (IGR) in the Treatment Approaches in Renal Cancer Global Evaluation Trial (TARGET) (sorafenib vs placebo, n=84) and the RECORD (everolimus vs placebo, n=43) phase 3 trials were analyzed. TGR was computed across clinically relevant periods: BEFORE treatment introduction (wash-out), UNDER (first cycle), at PROGRESSION (last cycle) and AFTER treatment discontinuation (washout). The association between TGR and outcome (overall survival [OS] and progression-free survival [PFS]) was computed in the entire TARGET cohort (n=903).

INTERVENTION

Sorafenib, everolimus, or placebo.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

TGR, RECIST, OS, and PFS rates.

RESULTS AND LIMITATIONS

Although nearly all the patients (IGR) were classified as stable disease (RECIST) after the first cycle, the great majority of the patients exhibited a decrease in TGR UNDER compared with BEFORE (sorafenib: p<0.00001; everolimus: p<0.00001). In sorafenib-treated but not in everolimus-treated patients (IGR), TGR at PROGRESSION (last cycle) was still lower than TGR BEFORE (washout) (p=0.012), while TGR AFTER progression (washout) was higher than TGR at PROGRESSION (last cycle) (p=0.0012). Higher TGR (first cycle) was associated with worse PFS (hazard ratio [HR]: 3.61; 95% confidence interval [CI], 2.45-5.34) and worse OS (HR: 4.69; 95% CI, 1.54-14.39), independently from the Motzer score and from the treatment arm in the entire TARGET cohort.

CONCLUSIONS

Computing TGR in mRCC patients is simple and provides clinically useful information for mRCC patients: (1) TGR is independently associated with prognosis (PFS, OS), (2) TGR allows for a subtle and quantitative characterization of drug activity at the first evaluation, and (3) TGR reveals clear drug-specific profiles at progression.

Volumetric tumor growth in advanced non-small cell lung cancer patients with EGFR mutations during EGFR-tyrosine kinase inhibitor therapy: developing criteria to continue therapy beyond RECIST progression

BACKGROUND

The objective of this study was to define the volumetric tumor growth rate in patients who had advanced nonsmall cell lung cancer (NSCLC) with sensitizing epidermal growth factor receptor (EGFR) mutations and had initially received treatment with EGFR-tyrosine kinase inhibitor (TKI) therapy beyond progression.

METHODS

The study included 58 patients with advanced NSCLC who had sensitizing EGFR mutations treated with first-line gefitinib or erlotinib, had baseline computed tomography (CT) scans available that revealed a measurable lung lesion, had at least 2 follow-up CT scans during TKI therapy, and had experienced volumetric tumor growth. The tumor volume (in mm3) of the dominant lung lesion was measured on baseline and follow-up CT scans during therapy. In total, 405 volume measurements were analyzed in a linear mixed-effects model, fitting time as a random effect, to define the growth rate of the logarithm of tumor volume (log(e)V).

RESULTS

A linear mixed-effects model was fitted to predict the growth of log(e)V, adjusting for time in months from baseline. Log(e)V was estimated as a function of time in months among patients whose tumors started growing after the nadir: log(e)V = 0.12*time  + 7.68. In this formula, the regression coefficient for time, 0.12/month, represents the growth rate of log(e)V (standard error, 0.015/month; P < .001). When adjusted for baseline volume, log(e)V0, the growth rate was also 0.12/month (standard error, 0.015/month; P < .001; log(e)V = 0.12*months + 0.72 log(e)V0 + 0.61).

CONCLUSIONS

Tumor volume models defined volumetric tumor growth after the nadir in patients with EGFR-mutant, advanced NSCLC who were receiving TKI, providing a reference value for the tumor growth rate in patients who progress after the nadir on TKI therapy. The results can be studied further in additional cohorts to develop practical criteria to help identify patients who are slowly progressing and can safely remain on EGFR-TKIs.

A new mathematical pharmacodynamic model of clonogenic cancer cell death by doxorubicin

Previous models for predicting tumor cell growth are mostly based on measurements of total cell numbers. The purpose of this paper is to provide a new simple mathematical model for calculating tumor cell growth focusing on the fraction of cells that is clonogenic. The non-clonogenic cells are considered to be relatively harmless. We performed a number of different types of experiments: a long-term drug "treatment", several concentrations/fixed time experiments and time-series experiments, in which human MCF-7 breast cancer cells were exposed to doxorubicin and the total number of cells were counted. In the latter two types, at every measurement point a plating efficiency experiment was started. The final number of colonies formed is equal to the number of clonogenic cells at the onset of the experiment. Based on the intracellular drug concentration, our model predicts cell culture effects taking clonogenic ability and growth inhibition by neighboring cells into account. The model fitted well to the experimental data. The estimated damage parameter which represents the chance of an MCF-7 cell to become non-clonogenic per unit time and per unit intracellular doxorubicin concentration was found to be 0.0025 ± 0.0008 (mean ± SD) nM(-1) h(-1). The model could be used to calculate the effect of every doxorubicin concentration versus time (C-t) profile. Although in vivo parameters may well be different from those found in vitro, the model can be used to predict trends, e.g. by comparing effects of different in vivo C-t profiles.

Sunitinib does not accelerate tumor growth in patients with metastatic renal cell carcinoma

Preclinical studies have suggested that sunitinib accelerates metastases in animals, ascribing this to inhibition of the vascular endothelial growth factor receptor or the tumor’s adaptation. To address whether sunitinib accelerates tumors in humans, we analyzed data from the pivotal randomized phase III trial comparing sunitinib and interferon alfa in patients with metastatic renal cell carcinoma. The evidence clearly shows that sunitinib was not harm- ful, did not accelerate tumor growth, and did not shorten survival. Specifically, neither longer sunitinib treatment nor a greater effect of sunitinib on tumors reduced survival. Sunitinib did reduce the tumor’s growth rate while administered, thereby improving survival, without appearing to alter tumor biology after discontinuation. Concerns arising from animal models do not apply to patients receiving sunitinib and likely will not apply to similar agents.

Estimation of renal cell carcinoma treatment effects from disease progression modeling

To improve future drug development efficiency in renal cell carcinoma (RCC), a disease-progression model was developed with longitudinal tumor size data from a phase III trial of sorafenib in RCC. The best-fit model was externally evaluated on 145 placebo-treated patients in a phase III trial of pazopanib; the model incorporated baseline tumor size, a linear disease-progression component, and an exponential drug effect (DE) parameter. With the model-estimated effect of sorafenib on RCC growth, we calculated the power of randomized phase II trials between sorafenib and hypothetical comparators over a range of effects. A hypothetical comparator with 80% greater DE than sorafenib would have 82% power (one-sided α = 0.1) with 50 patients per arm. Model-based quantitation of treatment effect with computed tomography (CT) imaging offers a scaffold on which to develop new, more efficient, phase II trial end points and analytic strategies for RCC.