Determination of an optimal response cut-off able to predict progression-free survival in patients with well-differentiated advanced pancreatic neuroendocrine tumours treated with sunitinib: an alternative to the current RECIST-defined response

Appropriate use of morphological imaging for assessing treatment response and disease progression of neuroendocrine tumors

Neuroendocrine tumors (NETs) are relatively rare neoplasms displaying heterogeneous clinical behavior, ranging from indolent to aggressive forms. Patients diagnosed with NETs usually receive a varied array of treatments, including somatostatin analogs, locoregional treatments (ablation, intra-arterial therapy), cytotoxic chemotherapy, peptide receptor radionuclide therapy (PRRT), and targeted therapies. To maximize therapeutic efficacy while limiting toxicity (both physical and economic), there is a need for accurate and reliable tools to monitor disease evolution and progression and to assess the effectiveness of these treatments. Imaging morphological methods, primarily relying on computed tomography (CT) and magnetic resonance imaging (MRI), are indispensable modalities for the initial evaluation and continuous monitoring of patients with NETs, therefore playing a pivotal role in gauging the response to treatment. The primary goal of assessing tumor response is to anticipate and weigh the benefits of treatments, especially in terms of survival gain. The World Health Organization took the pioneering step of introducing assessment criteria based on cross-sectional imaging. This initial proposal standardized the measurement of lesion sizes, laying the groundwork for subsequent criteria. The Response Evaluation Criteria in Solid Tumors (RECIST) subsequently refined and enhanced these standards, swiftly gaining acceptance within the oncology community. New treatments were progressively introduced, targeting specific features of NETs (such as tumor vascularization or expression of specific receptors), and achieving significant qualitative changes within tumors, although associated with minimal or paradoxical effects on tumor size. Several alternative criteria, adapted from those used in other cancer types and focusing on tumor viability, the slow growth of NETs, or refining the existing size-based RECIST criteria, have been proposed in NETs. This review article aims to describe and discuss the optimal utilization of CT and MRI for assessing the response of NETs to treatment; it provides a comprehensive overview of established and emerging criteria for evaluating tumor response, along with comparative analyses. Molecular imaging will not be addressed here and is covered in a dedicated article within this special issue.

Proposal of early CT morphological criteria for response of liver metastases to systemic treatments in gastroenteropancreatic neuroendocrine tumors: Alternatives to RECIST

RECIST 1.1 criteria are commonly used with computed tomography (CT) to evaluate the efficacy of systemic treatments in patients with neuroendocrine tumors (NETs) and liver metastases (LMs), but their relevance is questioned in this setting. We aimed to explore alternative criteria using different numbers of measured LMs and thresholds of size and density variation. We retrospectively studied patients with advanced pancreatic or small intestine NETs with LMs, treated with systemic treatment in the first-and/or second-line, without early progression, in 14 European expert centers. We compared time to treatment failure (TTF) between responders and non-responders according to various criteria defined by 0%, 10%, 20% or 30% decrease in the sum of LM size, and/or by 10%, 15% or 20% decrease in LM density, measured on two, three or five LMs, on baseline (≤1 month before treatment initiation) and first revaluation (≤6 months) contrast-enhanced CT scans. Multivariable Cox proportional hazard models were performed to adjust the association between response criteria and TTF on prognostic factors. We included 129 systemic treatments (long-acting somatostatin analogs 41.9%, chemotherapy 26.4%, targeted therapies 31.8%), administered as first-line (53.5%) or second-line therapies (46.5%) in 91 patients. A decrease ≥10% in the size of three LMs was the response criterion that best predicted prolonged TTF, with significance at multivariable analysis (HR 1.90; 95% CI: 1.06-3.40; p = .03). Conversely, response defined by RECIST 1.1 did not predict prolonged TTF (p = .91), and neither did criteria based on changes in LM density. A ≥10% decrease in size of three LMs could be a more clinically relevant criterion than the current 30% threshold utilized by RECIST 1.1 for the evaluation of treatment efficacy in patients with advanced NETs. Its implementation in clinical trials is mandatory for prospective validation. Criteria based on changes in LM density were not predictive of treatment efficacy. CLINICAL TRIAL REGISTRATION: Registered at CNIL-CERB, Assistance publique hopitaux de Paris as "E-NETNET-L-E-CT" July 2018. No number was assigned. Approved by the Medical Ethics Review Board of University Medical Center Groningen.

CT-based radiomics to distinguish progressive from stable neuroendocrine liver metastases treated with somatostatin analogues: an explorative study

BACKGROUND

Accurate response evaluation in patients with neuroendocrine liver metastases (NELM) remains a challenge. Radiomics has shown promising results regarding response assessment.

PURPOSE

To differentiate progressive (PD) from stable disease (SD) with radiomics in patients with NELM undergoing somatostatin analogue (SSA) treatment.

MATERIAL AND METHODS

A total of 46 patients with histologically confirmed gastroenteropancreatic neuroendocrine tumors (GEP-NET) with ≥1 NELM and ≥2 computed tomography (CT) scans were included. Response was assessed with Response Evaluation Criteria in Solid Tumors (RECIST1.1). Hepatic target lesions were manually delineated and analyzed with radiomics. Radiomics features were extracted from each NELM on both arterial-phase (AP) and portal-venous-phase (PVP) CT. Multiple instance learning with regularized logistic regression via LASSO penalization (with threefold cross-validation) was used to classify response. Three models were computed: (i) AP model; (ii) PVP model; and (iii) AP + PVP model for a lesion-based and patient-based outcome. Next, clinical features were added to each model.

RESULTS

In total, 19 (40%) patients had PD. Median follow-up was 13 months (range 1-50 months). Radiomics models could not accurately classify response (area under the curve 0.44-0.60). Adding clinical variables to the radiomics models did not significantly improve the performance of any model.

CONCLUSION

Radiomics features were not able to accurately classify response of NELM on surveillance CT scans during SSA treatment.

Maximum Value on Arterial Phase Computed Tomography Predicts Prognosis and Treatment Efficacy of Sunitinib for Pancreatic Neuroendocrine Tumours

PURPOSE

This study was designed to assess the computed tomography maximum (CTmax) value on pretherapeutic arterial phase computed tomography (APCT) images to predict pancreatic neuroendocrine tumours (pNETs) recurrence and clarify its role in predicting the outcome of tumour therapy.

METHODS

This retrospective study enrolled 250 surgical patients and 24 nonsurgical patients with sunitinib-based treatment in our hospital from 2008 to 2019. CT images were assessed, the maximum value was defined as "CTmax," and recurrence-free survival (RFS) or progression-free survival (PFS) was compared between a high-CTmax group and a low-CTmax group among patients who underwent surgical resection or nonsurgical, sunitinib-based treatment according to the CTmax cutoff value.

RESULTS

In ROC curve analysis, a CTmax of 108 Hounsfield units, as the cutoff value, achieved an AUC of 0.796 in predicting recurrence. Compared with the low-CTmax group, the high-CTmax group had a longer RFS (p < 0.001). Low CTmax was identified as an independent factor for RFS (p < 0.001) in multivariate analysis; these results were confirmed using the internal validation set. The CTmax value was significantly correlated with the microvascular density (MVD) value (p < 0.001) and the vascular endothelial growth factor receptor 2 (VEGFR2) score (p < 0.001). Furthermore, the high-CTmax group had a better PFS than the low-CTmax group among the sunitinib treatment group (p = 0.007).

CONCLUSIONS

The tumour CTmax on APCT might be a potential and independent indicator for predicting recurrence in patients who have undergone surgical resection and assessing the efficacy of sunitinib for patients with advanced metastatic pNETs.

Defining disease status in gastroenteropancreatic neuroendocrine tumors: Choi-criteria or RECIST?

PURPOSE

Adequate monitoring of changes in tumor load is fundamental for the assessment of the course of disease and response to treatment. There is an ongoing debate on the utility of RECIST v1.1 in gastroenteropancreatic neuroendocrine tumors (GEP-NETs).

METHODS

In this retrospective real-life cohort study, Choi-criteria were compared with RECIST v1.1. The agreement between both criteria and the association with survival endpoints were evaluated.

RESULTS

Seventy-five patients were included with a median follow-up of 35 months (range 8-53). Median progression-free survival (mPFS) according to RECIST v1.1 was 15 months (range 2-50) compared to 14 months (range 2-50) in Choi. According to RECIST, 33 (44%) patients were classified as having stable disease (SD), 40 (53%) as progressive disease (PD) and two (3%) patients as partial response (PR), compared to 9 (12%) patients classified as SD, 50 (67%) as PD and 16 (21%) as PR according to Choi-criteria. Overall concordance between the criteria was moderate (Cohen's Kappa = 0.408, p < 0.001) and agreement varied between 57 and 69% at each consecutive scan (p < 0.001). Survival analysis showed significant differences in overall survival (OS) for RECIST v1.1 categories PD and non-PD (log-rank p = 0.02), however, in Choi no significant differences in OS were found (p = 0.27).

CONCLUSION

RECIST v1.1 had a better clinical utility and prognostic value compared to Choi-criteria. Still, RECIST were also not sufficient to adequately predict OS. This outlines the need for new tools that provides accurate information on the disease course and treatment response to support precise prognostication in patients with GEP-NETs.

Predictive Factors for Resistant Disease with Medical/Radiologic/Liver-Directed Anti-Tumor Treatments in Patients with Advanced Pancreatic Neuroendocrine Neoplasms: Recent Advances and Controversies

Simple Summary

Tumor resistance, both primary and acquired, is leading to increased complexity in the nonsurgical treatment of patients with advanced panNENs, which would be greatly helped by reliable prognostic/predictive factors. The importance in identifying resistance is being contributed to by the increased array of possible treatments available for treating resistant advanced disease; the variable clinical course as well as response to any given treatment approach of patients within one staging or grading system, the advances in imaging which are providing increasing promising results/parameters that correlate with grading/outcome/resistance, the increased understanding of the molecular pathogenesis providing promising prognostic markers, all of which can contribute to selecting the best treatment to overcome resistance disease. Several factors have been identified that have prognostic/predictive value for identifying development resistant disease and affecting overall survival (OS)/PFS with various nonsurgical treatments of patients with advanced panNENs. Prognostic factors identified for patients with advanced panNENs for both OS/PFSs include various clinically-related factors (clinical, laboratory/biological markers, imaging, treatment-related factors), pathological factors (histological, classification, grading) and molecular factors. Particularly important prognostic factors for the different treatment modalities studies are the recent grading systems. Most prognostic factors for each treatment modality for OS/PFS are not specific for a given treatment option. These advances have generated several controversies and new unanswered questions, particularly those related to their possible role in predicting the possible sequence of different anti-tumor treatments in patients with different presentations. Each of these areas is reviewed in this paper.

Abstract

Purpose: Recent advances in the diagnosis, management and nonsurgical treatment of patients with advanced pancreatic neuroendocrine neoplasms (panNENs) have led to an emerging need for sensitive and useful prognostic factors for predicting responses/survival. Areas covered: The predictive value of a number of reported prognostic factors including clinically-related factors (clinical/laboratory/imaging/treatment-related factors), pathological factors (histological/classification/grading), and molecular factors, on therapeutic outcomes of anti-tumor medical therapies with molecular targeting agents (everolimus/sunitinib/somatostatin analogues), chemotherapy, radiological therapy with peptide receptor radionuclide therapy, or liver-directed therapies (embolization/chemoembolization/radio-embolization (SIRTs)) are reviewed. Recent findings in each of these areas, as well as remaining controversies and uncertainties, are discussed in detail, particularly from the viewpoint of treatment sequencing. Conclusions: The recent increase in the number of available therapeutic agents for the nonsurgical treatment of patients with advanced panNENs have raised the importance of prognostic factors predictive for therapeutic outcomes of each treatment option. The establishment of sensitive and useful prognostic markers will have a significant impact on optimal treatment selection, as well as in tailoring the therapeutic sequence, and for maximizing the survival benefit of each individual patient. In the paper, the progress in this area, as well as the controversies/uncertainties, are reviewed.

Optimization of the tumour response threshold in advanced gastroenteropancreatic neuroendocrine carcinomas treated with cisplatin/etoposide combined chemotherapy

OBJECTIVES

To identify early and more accurate imaging response criteria for computed tomography evaluation to define 'responders' in advanced gastroenteropancreatic neuroendocrine carcinoma (GEP-NEC) patients treated with cisplatin/etoposide combined chemotherapy.

MATERIALS AND METHODS

Thirty-seven patients with GEP-NEC treated with first-line cisplatin/etoposide (E/P) combined chemotherapy were enrolled in this study. Computed tomography scans of the chest, abdomen, and pelvis were performed at baseline, during the treatment course, and during follow-up. Tumour size was measured, and tumour response was evaluated by Response Evaluation Criteria in Solid Tumours (RECIST) 1.1. Receiver operating characteristic (ROC) analysis was carried out among the patients who progressed during follow-up. Thresholds from -55% to + 5% were tested by Kaplan-Meier analysis to define "responders" for significantly improved progression-free survival (PFS). The overall survival rate was compared between these two groups.

RESULTS

A reduction of 45% (vs. baseline) achieved the highest sensitivity (70%) and specificity (90%) by ROC analysis. This threshold divided patients into 15 responders and 22 nonresponders. Patients who were grouped as responders by the -45% threshold had a significantly longer PFS (11.06 months) than nonresponders (7.97 months, hazard ratio, 3.636; 95% confidence interval, 1.293-10.164). No significant difference was shown in overall survival between these two groups (29.1 vs. 21.4 months, P = 0.190).

CONCLUSION

A 45% reduction in target lesions may be considered to be a more reliable predictor than the RECIST 1.1 criteria in evaluating the outcome of GEP-NEC patients treated with E/P chemotherapy.

Are recist criteria adequate in assessing the response to therapy in metastatic NEN?

Response to therapy criteria, known as RECIST (Response Evaluation Criteria in Solid Tumours), are widely used to evaluate neuroendocrine tumours (NET) metastatic to the liver, under treatment. RECIST criteria does not take in account many various distinct features such as tumour growth, secretory capacity and anatomical localisation with wide variation in clinical and biological presentation of different NETs. Key features of RECIST includes definitions of the minimal size of measurable lesions, instructions on how many lesions to measure and follow, and the use of unidimensional, rather than bidimensional, measures for overall evaluation of tumour burden. These measures are currently done with computed tomography (CT) or Magnetic Resonance Imaging (MRI). RECIST criteria are accurate in assessing tumour progression but sometimes inaccurate in assessing tumour response after locoregional therapy or under molecular targeted therapy, tumour vessels being part of the target of such treatments. There is poor correlation between a so called tumour necrosis and conventional methods of response assessment, which poses questions of how best to quantify efficacy of these targeted therapies. Variations in tumour density with computed tomography (CT) could theoretically be associated with tumour necrosis. This hypothesis has been studied proposing alternative CT criteria of response evaluation in metastatic digestive NET treated with targeted therapy. If preliminary results upon the poor relationship between density measured with CT (derived from CHOI criteria) evolution curves at CT and PFS are confirmed by further studies, showing that the correlation between density changing and response to non-targeted treatment is weak, the use of contrast injection, will probably be not mandatory to enable appropriate evaluation.

Automatized Hepatic Tumor Volume Analysis of Neuroendocrine Liver Metastases by Gd-EOB MRI-A Deep-Learning Model to Support Multidisciplinary Cancer Conference Decision-Making

BACKGROUND

Rapid quantification of liver metastasis for diagnosis and follow-up is an unmet medical need in patients with secondary liver malignancies. We present a 3D-quantification model of neuroendocrine liver metastases (NELM) using gadoxetic-acid (Gd-EOB)-enhanced MRI as a useful tool for multidisciplinary cancer conferences (MCC).

METHODS

Manual 3D-segmentations of NELM and livers (149 patients in 278 Gd-EOB MRI scans) were used to train a neural network (U-Net architecture). Clinical usefulness was evaluated in another 33 patients who were discussed in our MCC and received a Gd-EOB MRI both at baseline and follow-up examination (n = 66) over 12 months. Model measurements (NELM volume; hepatic tumor load (HTL)) with corresponding absolute (ΔabsNELM; ΔabsHTL) and relative changes (ΔrelNELM; ΔrelHTL) between baseline and follow-up were compared to MCC decisions (therapy success/failure).

RESULTS

Internal validation of the model's accuracy showed a high overlap for NELM and livers (Matthew's correlation coefficient (φ): 0.76/0.95, respectively) with higher φ in larger NELM volume (φ = 0.80 vs. 0.71; p = 0.003). External validation confirmed the high accuracy for NELM (φ = 0.86) and livers (φ = 0.96). MCC decisions were significantly differentiated by all response variables (ΔabsNELM; ΔabsHTL; ΔrelNELM; ΔrelHTL) (p < 0.001). ΔrelNELM and ΔrelHTL showed optimal discrimination between therapy success or failure (AUC: 1.000; p < 0.001).

CONCLUSION

The model shows high accuracy in 3D-quantification of NELM and HTL in Gd-EOB-MRI. The model's measurements correlated well with MCC's evaluation of therapeutic response.

Clinical and Translational Research Challenges in Neuroendocrine Tumours

Neuroendocrine tumours (NETs) represent a range of neoplasms that may arise from any (neuro)endocrine cell situated in any part of the human body. As any other rare diseases, NETs face several difficulties in relation to research. This review will describe some of the main challenges and proposed solutions faced by researchers with expertise in rare malignancies. Some of the most common challenges in clinical and translational research are enumerated in this review, covering aspects from clinical, translational and basic research. NETs being a heterogeneous group of diseases and a limited sample size of clinical and translational research projects are the main challenges. Challenges with NETs lay over the disparities between healthcare models to tackle rare diseases. NETs add an extra layer of complexity due to a numerous group of different entities. Prospective real-world data trials are an opportunity for rare cancers with the revolution of electronic health technologies. This review explores potential solutions to these challenges that could be useful not only to the NET community but also to other rare tumours researchers.

Systemic Treatment Selection for Patients with Advanced Pancreatic Neuroendocrine Tumours (PanNETs)

Pancreatic neuroendocrine tumours (PanNETs) are rare diseases and a good example of how research is not only feasible, but also of crucial importance in the scenario of rare tumours. Many clinical trials have been performed over the past two decades expanding therapeutic options for patients with advanced PanNETs. Adequate management relies on optimal selection of treatment, which may be challenging for clinicians due to the fact that multiple options of therapy are currently available. A number of therapies already exist, which are supported by data from phase III studies, including somatostatin analogues and targeted therapies (sunitinib and everolimus). In addition, chemotherapy remains an option, with temozolomide and capecitabine being one of the most popular doublets to use. Peptide receptor radionuclide therapy was successfully implemented in patients with well-differentiated gastro-entero-pancreatic neuroendocrine tumours, but with certain questions waiting to be solved for the management of PanNETs. Finally, the role of immunotherapy is still poorly understood. In this review, the data supporting current systemic treatment options for locally advanced or metastatic PanNETs are summarized. Strategies for treatment selection in patients with PanNETs based on patient, disease, or drug characteristics is provided, as well as a summary of current evidence on prognostic and predictive biomarkers. Future perspectives are discussed, focusing on current and forthcoming challenges and unmet needs of patients with these rare tumours.

Neoadjuvant Capecitabine/Temozolomide for Locally Advanced or Metastatic Pancreatic Neuroendocrine Tumors

OBJECTIVES

The combination chemotherapy regimen capecitabine/temozolomide (CAPTEM) is efficacious for metastatic well-differentiated pancreatic neuroendocrine tumors (PNETs), but its role in the neoadjuvant setting has not been established.

METHODS

The outcomes of all patients with locally advanced or resectable metastatic PNETs who were treated with neoadjuvant CAPTEM between 2009 and 2017 at 2 high-volume institutions were retrospectively reviewed.

RESULTS

Thirty patients with locally advanced PNET (n = 10) or pancreatic neuroendocrine hepatic metastases (n = 20) received neoadjuvant CAPTEM. Thirteen patients (43%) exhibited partial radiographic response (PR), 16 (54%) had stable disease, and 1 (3%) developed progressive disease. Twenty-six (87%) patients underwent resection (pancreatectomy [n = 12], combined pancreatectomy and liver resection [n = 8], or major hepatectomy alone [n = 6]); 3 (18%) declined surgery despite radiographic PR, and 1 (3%) underwent aborted pancreatoduodenectomy. Median primary tumor size was 5.5 cm, and median Ki-67 index was 3.5%. Rates of PR were similar across tumor grades (P = 0.24). At median follow-up of 49 months, median progression-free survival was 28.2 months and 5-year overall survival was 63%.

CONCLUSIONS

Neoadjuvant CAPTEM is associated with favorable radiographic objective response rates for locally advanced or metastatic PNET and may facilitate selection of patients appropriate for surgical resection.

Evaluating radiological response in pancreatic neuroendocrine tumours treated with sunitinib: comparison of Choi versus RECIST criteria (CRIPNET_ GETNE1504 study)

BACKGROUND

The purpose of our study was to analyse the usefulness of Choi criteria versus RECIST in patients with pancreatic neuroendocrine tumours (PanNETs) treated with sunitinib.

METHOD

A multicentre, prospective study was conducted in 10 Spanish centres. Computed tomographies, at least every 6 months, were centrally evaluated until tumour progression.

RESULTS

One hundred and seven patients were included. Median progression-free survival (PFS) by RECIST and Choi were 11.42 (95% confidence interval [CI], 9.7-15.9) and 15.8 months (95% CI, 13.9-25.7). PFS by Choi (Kendall's τ = 0.72) exhibited greater correlation with overall survival (OS) than PFS by RECIST (Kendall's τ = 0.43). RECIST incorrectly estimated prognosis in 49.6%. Partial response rate increased from 12.8% to 47.4% with Choi criteria. Twenty-four percent of patients with progressive disease according to Choi had stable disease as per RECIST, overestimating treatment effect. Choi criteria predicted PFS/OS. Changes in attenuation occurred early and accounted for 21% of the variations in tumour volume. Attenuation and tumour growth rate (TGR) were associated with improved survival.

CONCLUSION

Choi criteria were able to capture sunitinib's activity in a clinically significant manner better than RECIST; their implementation in standard clinical practice shall be strongly considered in PanNET patients treated with this drug.

Prediction of Progression-Free Survival in Patients With Advanced, Well-Differentiated, Neuroendocrine Tumors Being Treated With a Somatostatin Analog: The GETNE-TRASGU Study

PURPOSE

Somatostatin analogs (SSAs) are recommended for the first-line treatment of most patients with well-differentiated, gastroenteropancreatic (GEP) neuroendocrine tumors; however, benefit from treatment is heterogeneous. The aim of the current study was to develop and validate a progression-free survival (PFS) prediction model in SSA-treated patients.

PATIENTS AND METHODS

We extracted data from the Spanish Group of Neuroendocrine and Endocrine Tumors Registry (R-GETNE). Patient eligibility criteria included GEP primary, Ki-67 of 20% or less, and first-line SSA monotherapy for advanced disease. An accelerated failure time model was developed to predict PFS, which was represented as a nomogram and an online calculator. The nomogram was externally validated in an independent series of consecutive eligible patients (The Christie NHS Foundation Trust, Manchester, United Kingdom).

RESULTS

We recruited 535 patients (R-GETNE, n = 438; Manchester, n = 97). Median PFS and overall survival in the derivation cohort were 28.7 (95% CI, 23.8 to 31.1) and 85.9 months (95% CI, 71.5 to 96.7 months), respectively. Nine covariates significantly associated with PFS were primary tumor location, Ki-67 percentage, neutrophil-to-lymphocyte ratio, alkaline phosphatase, extent of liver involvement, presence of bone and peritoneal metastases, documented progression status, and the presence of symptoms when initiating SSA. The GETNE-TRASGU (Treated With Analog of Somatostatin in Gastroenteropancreatic and Unknown Primary NETs) model demonstrated suitable calibration, as well as fair discrimination ability with a C-index value of 0.714 (95% CI, 0.680 to 0.747) and 0.732 (95% CI, 0.658 to 0.806) in the derivation and validation series, respectively.

CONCLUSION

The GETNE-TRASGU evidence-based prognostic tool stratifies patients with GEP neuroendocrine tumors receiving SSA treatment according to their estimated PFS. This nomogram may be useful when stratifying patients with neuroendocrine tumors in future trials. Furthermore, it could be a valuable tool for making treatment decisions in daily clinical practice.

Tumor Growth Rate as a Validated Early Radiological Biomarker Able to Reflect Treatment-Induced Changes in Neuroendocrine Tumors: The GREPONET-2 Study

PURPOSE

Tumor growth rate (TGR) represents the percentage change in tumor volume per month (%/m). Previous results from the GREPONET study showed that TGR measured after 3 months (TGR_3m) of starting systemic treatment (ST) or watch and wait (WW) was an early biomarker predicting progression-free survival (PFS) in neuroendocrine tumors (NET).

EXPERIMENTAL DESIGN

Patients from 7 centers with advanced grade (G) 1/2 NETs from the pancreas (P)/small bowel (SB) initiating ST/WW were eligible. Computed tomography (CT)/MRI performed at prebaseline, baseline, and 3(±1) months of study entry were retrospectively reviewed. Aim-1: explore treatment-induced changes in TGR (ΔTGR_3m-BL; paired T test), and Aim-2: validate TGR_3m (<0.8%/m vs. ≥0.8%/m) as an early biomarker in an independent cohort (Kaplan-Meier/Cox regression).

RESULTS

Of 785 patients screened, 127 were eligible. Mean (SD) TGR₀ and TGR_3m were 5.4%/m (14.9) and -1.4%/m (11.8), respectively. Mean (SD) ΔTGR_3m-BL paired-difference was -6.8%/m (19.3; P < 0.001). Most marked ΔTGR_3m-BL [mean (SD)] were identified with targeted therapies [-11.3%/m (4.7); P = 0.0237] and chemotherapy [-7.9%/m (3.4); P = 0.0261]. Multivariable analysis confirmed the absence of previous treatment (OR = 4.65; 95% CI, 1.31-16.52; P = 0.018) and low TGR_3m (continuous variable; OR 1.09; 95% CI, 1.01-1.19; P = 0.042) to be independent predictors of radiologic objective response. When the multivariable survival analysis for PFS (Cox regression) was adjusted to grade (P = 0.004) and stage (P = 0.017), TGR_3m ≥ 0.8 (vs. <0.8) maintained its significance as a prognostic factor (P < 0.001), whereas TGR₀ and ΔTGR_3m-BL did not. TGR_3m ≥ 0.8%/m was confirmed as an independent prognostic factor for PFS [external validation; Aim-2; multivariable HR 2.21 (95% CI, 1.21-3.70; P = 0.003)].

CONCLUSIONS

TGR has a role as a biomarker for monitoring response to therapy for early identification of treatment-induced changes and for early prediction of PFS and radiologic objective response.

Analysis of response-related endpoints in trials of first-line medical treatment of metastatic colorectal cancer

BACKGROUND

Tumor radiologic response after systemic chemotherapy has been used as endpoint of trials of patients with metastatic colorectal cancer (mCRC), which can report the best overall response rate (ORR) and the disease control rate (DCR) by RECIST criteria as well as the early tumor shrinkage (ETS). The present study perform a trial-level analysis to verify whether such response-related endpoints are predictive of overall survival (OS).

METHODS

After a systematic search, randomized clinical trials (RCTs) were selected each time they evaluated the three response endpoints and progression-free survival (PFS). Two arms per trial were selected, and the correlation between the difference in each endpoint and the difference in OS was calculated. The analysis then evaluated the effects of treatment on ∆ORR, or ∆DCR, ∆ETS, ∆PFS, and on ∆OS, using separate linear regressions for each of them, and the proportion of variability explained (R²_trial) on OS for each of the four endpoints was calculated.

RESULTS

The systematic review of the literature led to the selection of 12 RCTs, 7 phase-3 and 5 phase-2. ETS reported a different performance in the entire sample compared to phase-3 trials (R²_trial = 0.172 vs. 0.842), differently from DCR (R²_trial = 0.541 vs. 0.816) and ORR (R²_trial = 0.349 vs. 0.740). Surprisingly, PFS predicted OS with a weak correlation, which was not significant in the subgroup of phase-3 studies (R²_trial = 0.455 vs. 0.466).

CONCLUSION

The results of the present trial-level analysis report a good performance of two response-related endpoints, DCR and ETS, and suggest that they could be differently used depending on the setting of disease and the type of medical treatment.

Value of Tumor Growth Rate (TGR) as an Early Biomarker Predictor of Patients' Outcome in Neuroendocrine Tumors (NET)-The GREPONET Study

INTRODUCTION

Tumor growth rate (TGR; percent size change per month [%/m]) is postulated to be an early radiological biomarker to overcome limitations of RECIST. This study aimed to assess the impact of TGR in neuroendocrine tumors (NETs) and potential clinical and therapeutic applications.

MATERIALS AND METHODS

Patients (pts) with advanced grade (G) 1/2 NETs from the pancreas or small bowel initiating systemic treatment (ST) or watch and wait (WW) were eligible. Baseline and follow-up scans were retrospectively reviewed to calculate TGR at pretreatment (TGR₀), first follow-up (TGR_first), and 3(±1) months of study entry (TGR_3m).

RESULTS

Out of 905 pts screened, 222 were eligible. Best TGR_first (222 pts) cutoff was 0.8 (area under the curve, 0.74). When applied to TGR_3m (103 pts), pts with TGR_3m <0.8 (66.9%) versus TGR_3m ≥ 0.8 (33.1%) had longer median progression-free survival (PFS; 26.3 m; 95% confidence interval [CI] 19.5-32.4 vs. 9.3 m; 95% CI, 6.1-22.9) and lower progression rate at 12 months (7.3% vs. 56.8%; p = .001). WW (vs. ST) and TGR_3m ≥ 0.8 (hazard ratio [HR], 3.75; 95% CI, 2.21-6.34; p < .001) were retained as factors associated with a shorter PFS in multivariable Cox regression. TGR_3m (HR, 3.62; 95% CI, 1.97-6.64; p < .001) was also an independent factor related to shorter PFS when analysis was limited to pts with stable disease (81 pts). Out of the 60 pts with TGR₀ data available, 60% of pts had TGR₀ < 4%/month. TGR₀ ≥ 4 %/month (HR, 2.22; 95% CI, 1.15-4.31; p = .018) was also an independent factor related to shorter PFS.

CONCLUSION

TGR is an early radiological biomarker able to predict PFS and to identify patients with advanced NETs who may require closer radiological follow-up.

IMPLICATIONS FOR PRACTICE

Tumor growth rate at 3 months (TGR_3m) is an early radiological biomarker able to predict progression-free survival and to identify patients with advanced neuroendocrine tumors who may require closer radiological follow-up. It is feasible to calculate TGR_3m in clinical practice and it could be a useful tool for guiding patient management. This biomarker could also be implemented in future clinical trials to assess response to therapy.

Are tumor size changes predictive of survival for checkpoint blockade based immunotherapy in metastatic melanoma?

BACKGROUND

In oncology clinical development, objective response rate, disease control rate and early tumor size changes are commonly used as efficacy metrics for early decision-making. However, for immunotherapy trials, it is unclear whether these early efficacy metrics are still predictive of long-term clinical benefit such as overall survival. The goal of this paper is to identify appropriate early efficacy metrics predictive of overall survival for immunotherapy trials.

METHODS

Based on several checkpoint blockade based immunotherapy studies in metastatic melanoma, we evaluated the predictive value of early tumor size changes and RECIST-based efficacy metrics at various time points on overall survival. The cut-off values for tumor size changes to predict survival were explored via tree based recursive partitioning and validated by external data. Sensitivity analyses were performed for the cut-offs.

RESULTS

The continuous tumor size change metric and RECIST-based trichotomized response metric at different landmark time points were found to be statistically significantly associated with overall survival. The predictive values were higher at Week 12 and 18 than those at Week 24. The percentage of tumor size changes appeared to have comparable or lower predictive values than the RECIST-based trichotomized metric, and a cut-off of approximately 10% tumor reduction appeared to be reasonable for predicting survival.

CONCLUSIONS

An approximate 10% tumor reduction may be a reasonable cut-off for early decision-making while the RECIST-based efficacy metric remains the primary tool. Early landmark analysis is especially useful for decision making when accrual is fast. Composite response rate (utilizing different weights for PR/CR and SD) may be worth further investigation.

TRIAL REGISTRATION

Clinical trials gov, NCT01295827 , Registered February 15, 2011; NCT01704287 , Registered October 11, 2012; NCT01866319 , Registered May 31, 2013.