Exploring Genetic Variants and Platinum Chemotherapy Response in Indonesian Non-Small Cell Lung Cancer Patients: Insights from ERCC2 rs13181.

Purpose: Individual responses to platinum-based treatment for Non-Small Cell Lung Cancer (NSCLC) are influenced by genetic polymorphisms, including Single Nucleotide Polymorphisms (SNPs). This study aimed to explore the role of ERCC2 in the Nucleotide Excision Repair (NER) pathway for platinum-based chemotherapy in NSCLC. While ERCC2 is widely studied, data for Southeast Asian populations are lacking. Addressing this gap could improve personalized treatment strategies for NSCLC in this demographic. Patients and Methods: This study recruited 82 NSCLC patients with wildtype mutations of EGFR at Dr. H.A. Rotinsulu Lung Hospital, Bandung, and Dharmais Cancer Hospital, Jakarta. Data were collected prospectively from whole blood samples and medical records, while the effectiveness of chemotherapy was assessed by evaluating the response using RECIST 1.1 criteria on fourth cycle of chemotherapy. Results: The results of this study showed the presence of genotype variation among the subjects, with frequency distribution as follows: AA genotype (82.9%), AC genotype (15.9%), and CC genotype (1.2%). The analysis of the association between ERCC2 rs13181 CC + AC versus AA with RECIST 1.1 yielded an odds ratio (OR) of 1.042 (95% CI: 0.292-3.715; p=0.950). A multivariate analysis that included cancer stage and chemotherapy regimen as additional variables produced an adjusted odds ratio (aOR) of 0.970 (95% CI: 0.263-3.568; p=0.963). Conclusion: This study did not find statistically significant associations between ERCC2 rs13181 polymorphisms and chemotherapy responses. However, this research highlights the presence of genetic variation within the Indonesian population, with the AA genotype being the most prevalent, which may influence chemotherapy responses. The results provided preliminary data and lay the foundation for future comprehensive cohort observational investigations.

Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer.

BACKGROUND: Elevated microRNA-155 (miR-155) expression in non-small-cell lung cancer (NSCLC) promotes cisplatin resistance and negatively impacts treatment outcomes. However, miR-155 can also boost anti-tumor immunity by suppressing PD-L1 expression. Therapeutic targeting of miR-155 through its antagonist, anti-miR-155, has proven challenging due to its dual molecular effects. METHODS: We developed a multiscale mechanistic model, calibrated with in vivo data and then extrapolated to humans, to investigate the therapeutic effects of nanoparticle-delivered anti-miR-155 in NSCLC, alone or in combination with standard-of-care drugs. RESULTS: Model simulations and analyses of the clinical scenario revealed that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks has substantial anti-cancer activity. It led to a median progression-free survival (PFS) of 6.7 months, which compared favorably to cisplatin and immune checkpoint inhibitors. Further, we explored the combinations of anti-miR-155 with standard-of-care drugs, and found strongly synergistic two- and three-drug combinations. A three-drug combination of anti-miR-155, cisplatin, and pembrolizumab resulted in a median PFS of 13.1 months, while a two-drug combination of anti-miR-155 and cisplatin resulted in a median PFS of 11.3 months, which emerged as a more practical option due to its simple design and cost-effectiveness. Our analyses also provided valuable insights into unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimens to prevent antagonistic effects. CONCLUSIONS: This work bridges the gap between preclinical development and clinical translation of anti-miR-155 and unravels the potential of anti-miR-155 combination therapies in NSCLC.

RECIST 1.1 assessments variability: a systematic pictorial review of blinded double reads.

Reader variability is intrinsic to radiologic oncology assessments, necessitating measures to enhance consistency and accuracy. RECIST 1.1 criteria play a crucial role in mitigating this variability by standardizing evaluations, aiming to establish an accepted "truth" confirmed by histology or patient survival. Clinical trials utilize Blind Independent Centralized Review (BICR) techniques to manage variability, employing double reads and adjudicators to address inter-observer discordance effectively. It is essential to dissect the root causes of variability in response assessments, with a specific focus on the factors influencing RECIST evaluations. We propose proactive measures for radiologists to address variability sources such as radiologist expertise, image quality, and accessibility of contextual information, which significantly impact interpretation and assessment precision. Adherence to standardization and RECIST guidelines is pivotal in diminishing variability and ensuring uniform results across studies. Variability factors, including lesion selection, new lesion appearance, and confirmation bias, can have profound implications on assessment accuracy and interpretation, underscoring the importance of identifying and addressing these factors. Delving into the causes of variability aids in enhancing the accuracy and consistency of response assessments in oncology, underscoring the role of standardized evaluation protocols and mitigating risk factors that contribute to variability. Access to contextual information is crucial. CRITICAL RELEVANCE STATEMENT: By understanding the causes of diagnosis variability, we can enhance the accuracy and consistency of response assessments in oncology, ultimately improving patient care and clinical outcomes. KEY POINTS: Baseline lesion selection and detection of new lesions play a major role in the occurrence of discordance. Image interpretation is influenced by contextual information, the lack of which can lead to diagnostic uncertainty. Radiologists must be trained in RECIST criteria to reduce errors and variability.

Pooled Rate of Pseudoprogression, Patterns of Response, and Tumor Burden Analysis in Patients Undergoing Immunotherapy Oncologic Trials for Different Malignancies.

AIMS: Assess rates of true pseudoprogression in unconfirmed progressive disease (iUPD) in a pool of immunotherapy clinical trials for different cancers, analyze tumor characteristics that drive iUPD classification, and investigate potentials predictors of pseudoprogression. MATERIALS AND METHODS: Retrospective interpretation of prospectively acquired data. Patients from 18 immunotherapy clinical trials with two arms (RECIST 1.1, iRECIST), of 10 cancer types were selected. Pooled rate of true pseudoprogression among iUPD was estimated using a common effect meta-analysis. Target, Non-target, and new lesions as the trigger of confirmed-vs pseudo-progression were compared using Chi-Square and Fisher exact tests. Conditional logistic regression was used to investigate the association between age, sex, tumor burden at baseline, and number of follow ups and pseudoprogression. RESULTS: 60/287 (21%) patients (17 women) were classified as iUPD with at least one subsequent confirmatory timepoint. The overall pooled estimate of pseudoprogression was 15% (95%CI: 8%--26%). Nontarget lesions were significantly more frequent the cause of iUPD than change in Target lesions size (p< 0.001). Most observations of true pseudoprogression occurred in the first follow-up (77%), whereas confirmed progression occurred in later time points during the trial. Pseudoprogression was not significantly associated with age, sex, tumor burden at baseline, or number of timepoints. CONCLUSION: In a pool of immunotherapy trials, the rate of true pseudoprogression was 15%, most often in the first timepoint after baseline than later in treatment. iUPD categorization was mostly driven by changes in NT lesions rather than objective changes in measurements of target lesions.

Translational modeling-based evidence for enhanced efficacy of standard-of-care drugs in combination with anti-microRNA-155 in non-small-cell lung cancer.

Elevated microRNA-155 (miR-155) expression in non-small-cell lung cancer (NSCLC) promotes cisplatin resistance and negatively impacts treatment outcomes. However, miR-155 can also boost anti-tumor immunity by suppressing PD-L1 expression. We developed a multiscale mechanistic model, calibrated with in vivo data and then extrapolated to humans, to investigate the therapeutic effects of nanoparticle-delivered anti-miR-155 in NSCLC, alone or in combination with standard-of-care drugs. Model simulations and analyses of the clinical scenario revealed that monotherapy with anti-miR-155 at a dose of 2.5 mg/kg administered once every three weeks has substantial anti-cancer activity. It led to a median progression-free survival (PFS) of 6.7 months, which compared favorably to cisplatin and immune checkpoint inhibitors. Further, we explored the combinations of anti-miR-155 with standard-of-care drugs, and found strongly synergistic two- and three-drug combinations. A three-drug combination of anti-miR-155, cisplatin, and pembrolizumab resulted in a median PFS of 13.1 months, while a two-drug combination of anti-miR-155 and cisplatin resulted in a median PFS of 11.3 months, which emerged as a more practical option due to its simple design and cost-effectiveness. Our analyses also provided valuable insights into unfavorable dose ratios for drug combinations, highlighting the need for optimizing dose regimen to prevent antagonistic effects. Thus, this work bridges the gap between preclinical development and clinical translation of anti-miR-155 and unravels the potential of anti-miR-155 combination therapies in NSCLC.

Circulating miRNA-21 Levels in Breast Cancer Patients Before and After Chemotherapy and Its Association with Clinical Improvement.

Breast cancer is the most frequent type of cancer in women, many patients experience recurrences and metastasis. miR-21 (microRNA-21) as biomarker is under investigation for breast cancer. At present, there is very limited information available regarding effect of chemotherapy on miR-21 expression in breast cancer and its correlation with the clinical improvement. Hence, this study was planned to evaluate the effect of chemotherapy on miR-21 in metastatic breast cancer and its relationship with the clinical outcome. Females, aged-18-90 years diagnosed with Invasive Ductal Carcinoma of breast and candidate of neoadjuvant chemotherapy including Adriamycin (60 mg/m2), Cyclophosphamide (600 mg/m2) with or without Taxane (75-175 mg/m2) were included in the study. Before and after 42 days of staring of chemotherapy sample was collected for circulatory miR-21 and RECIST 1.1 criteria was applied to assess the clinical status. Blood samples for routine clinical biomarkers including liver function test and renal function tests was also collected. miR-21 expression before and after chemotherapy was assessed using standard method based on real time PCR. Expression of miR-21, RECIST criteria and other liver and kidney related biomarkers were compared before and after chemotherapy. After neoadjuvant chemotherapy expression of miR-21 was significantly increased by 5.65-fold. There was significant improvement in clinical scores based on RECIST criteria (0.046). No significant correlation was observed between miR-21 expression and difference in RECIST score (r = - 0.122, p = 0.570). Neoadjuvant chemotherapy causes clinical improvement in breast cancer patients however it is not correlated with the miR-21 expression which significantly increased after chemotherapy.

A perspective: the integration of ctDNA into Response Evaluation Criteria in Solid Tumours 1.1 for phase II immunotherapy clinical trials.

A consensus guideline, iRECIST, was developed by the Response Evaluation Criteria in Solid Tumours (RECIST) working group for the use of the modified RECIST version 1.1 in cancer immunotherapy trials. iRECIST was designed to separate pseudoprogression from real progression. However, this is not the only ambiguous situation. In clinical immunotherapy trials, stable disease may reflect three tumor responses, including real stable disease, progressive disease and responsive disease. The prediction of a "true complete/partial response" is also important. Much data has accumulated showing that ctDNA can guide decisions at this point; thus, integrating ctDNA into the RECIST 1.1 criteria may help to distinguish a true tumor response type earlier in patients treated with immunotherapy; however, prospectively designed validation studies are needed.

Modified response evaluation criteria in solid tumors: A better response evaluation criteria for patients with non-squamous non-small cell lung cancer after bevacizumab treatment.

AIM: Cavitation of lesions is common in non-squamous non-small cell lung cancer (non-squamous-NSCLC) patients treated with vascular endothelial growth factor receptor tyrosine kinase inhibitors (VEGFRIs). However, traditional response evaluation criteria in solid tumors (RECIST) do not take cavitation into consideration and may no longer be accurate for potentially reflecting the real clinical efficacy of anti-vessel growth therapy. Here, we aimed to optimize the traditional RECIST version 1.1 by adding cavitation into the evaluation criteria. METHODS: We performed a post-hoc radiologic review of 517 patients in a phase III clinical trial of bevacizumab biosimilar (SIBP04) combined with chemotherapy for the treatment of non-squamous NSCLC. Tumor responses were assessed by RECIST1.1 and mRECIST criteria (modified RECIST, a novel alternate method where the longest diameter of the cavity was subtracted from the overall longest diameter of that lesion to measure target lesions), respectively, and correlated with clinical outcomes. RESULTS: Cavitations of pulmonary lesions were seen in nine (2%) patients at baseline, and 97 (19%) during treatment. The use of mRECIST resulted in an alteration of the response category. For patients with post-therapy cavitation, the objective response rate was 56% using RECIST1.1 and 67% by mRECIST. In addition, the survival rates between partial response, stable disease, and progressive disease when the mRECIST was applied were significantly different (p < 0.05), while RECIST1.1 failed to show survival differences (p = 0.218). CONCLUSION: For patients with post-therapy cavitation, mRECIST exhibited higher predictability of survival than RECIST1.1. Response assessment might be improved by incorporating cavitation into assessment, potentially altering outcomes of key clinical efficacy parameters.

Influence of Tumor Cavitation on Assessing the Clinical Benefit of Anti-PD1 or PD-L1 Inhibitors in Advanced Lung Squamous Cell Carcinoma.

PURPOSE: A considerable portion of lung squamous cell cancer (LUSC) displays radiographic signs of cavitation. The cavitation of lesions is not accounted for in the prevailing Evaluation Criteria of Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 or iRECIST in lung cancer. We hypothesized that cavitation might alter response assessment in these patients. PATIENTS AND METHODS: We performed a retrospective radiologic review of 785 patients with stage IV LUSC treated with PD-1/PD-L1 antibody combined with platinum-based doublet chemotherapy. 131 patients exhibited cavitation lesions pre- or after-treatment. Response was assessed by RECIST v1.1 and a modified Evaluation Criteria in Solid Tumors (mRECIST) guidelines in which the longest diameter of any cavity was subtracted from the overall longest diameter of that lesion to measure target lesions. The response rate and PFS and OS between mRECIST and RECIST v1.1 were compared. Survival curves of different response categories in each criterion were prepared using the method of Kaplan-Meier and log-rank tests. Weighted κ statistics were used to assess interobserver reproducibilities and to compare response rates. The chi-square test confirmed the relationship between PD-L1 expression and post-treatment cavitation. RESULTS: Notable cavitation of pulmonary lesions was seen in 16.7% of 785 patients treated with immunotherapy combined with platinum-based chemotherapy. Using the mRECIST for response assessment resulted in a higher response rate than RECIST v1.1 (66% vs. 57%). mRECIST might better identify patients with PFS and OS benefits who have cavitation. The chi-square test revealed a marginally significant difference between PD-L1 expression and tumor cavitation. Interobserver reproducibility of mRECIST for tumor cavitation evaluation was acceptable (the weighted k coefficients for mRECIST criteria was 0.821). CONCLUSION: Cavitation lesions at baseline and after checkpoint treatment are common in LUSC patients. mRECIST records a significantly higher response rate than RECIST for these LUSC patients. Response assessment might be improved by incorporating cavitation into volume assessment for target lesions. These results may inform further modifications to RECIST V1.1 to better reflect efficacy with immunotherapy.

A European Society of Oncologic Imaging (ESOI) survey on the radiological assessment of response to oncologic treatments in clinical practice.

OBJECTIVES: To present the results of a survey on the assessment of treatment response with imaging in oncologic patient, in routine clinical practice. The survey was promoted by the European Society of Oncologic Imaging to gather information for the development of reporting models and recommendations. METHODS: The survey was launched on the European Society of Oncologic Imaging website and was available for 3 weeks. It consisted of 5 sections, including 24 questions related to the following topics: demographic and professional information, methods for lesion measurement, how to deal with diminutive lesions, how to report baseline and follow-up examinations, which previous studies should be used for comparison, and role of RECIST 1.1 criteria in the daily clinical practice. RESULTS: A total of 286 responses were received. Most responders followed the RECIST 1.1 recommendations for the measurement of target lesions and lymph nodes and for the assessment of tumor response. To assess response, 48.6% used previous and/or best response study in addition to baseline, 25.2% included the evaluation of all main time points, and 35% used as the reference only the previous study. A considerable number of responders used RECIST 1.1 criteria in daily clinical practice (41.6%) or thought that they should be always applied (60.8%). CONCLUSION: Since standardized criteria are mainly a prerogative of clinical trials, in daily routine, reporting strategies are left to radiologists and oncologists, which may issue local and diversified recommendations. The survey emphasizes the need for more generally applicable rules for response assessment in clinical practice. CRITICAL RELEVANCE STATEMENT: Compared to clinical trials which use specific criteria to evaluate response to oncological treatments, the free narrative report usually adopted in daily clinical practice may lack clarity and useful information, and therefore, more structured approaches are needed. KEY POINTS: · Most radiologists consider standardized reporting strategies essential for an objective assessment of tumor response in clinical practice. · Radiologists increasingly rely on RECIST 1.1 in their daily clinical practice. · Treatment response evaluation should require a complete analysis of all imaging time points and not only of the last.

Comparison of RECIST and iRECIST criteria in patients with advanced lung cancer treated with nivolumab.

Background: Systemic therapy in lung cancer is mainstay of treatment as most patients present in advanced stages, with rising importance of new immunotherapy agents. Purpose: To compare the RECIST 1.1 and the immunotherapy Response Evaluation Criteria in Solid Tumors (iRECISTs) criteria for response assessment in lung cancer patients on immunotherapy. To find the incidence of pseudoprogression and associated imaging patterns. Material and Methods: Retrospective study in 28 patients treated with immunotherapy for advanced metastatic NSCLC. End points were progression-free survival (PFS) and overall survival (OS). Response assessments were separately tabulated according to RECIST 1.1 and iRECIST and classified into dichotomous groups of responders and nonresponders. Agreement in assessments between RECIST 1.0 and iRECIST examined using Cohen kappa (κ) coefficient with 95% confidence intervals. Kaplan-Meier survival analysis was done for PFS and OS. Differences between RECIST 1.1 and iRECIST for both responder and nonresponder were evaluated by the log rank test, Breslow (Generalized Wilcoxon) test, and Tarone-Ware test. Results: Incidence of pseudoprogression was 7% (2/28). The RECIST1.1 and iRECIST were in disagreement in two patients. The agreement between RECIST and iRECIST was almost perfect. The PFS and the OS are significantly longer in duration for responders in comparison to nonresponders for both RECIST and iRECIST and the difference between two assessment criteria is not significant. Conclusion: Although iRECIST aims to monitor treatment more precisely than conventional response criteria, this must be weighed against how infrequent pseudoprogression is and the cost of this therapy, both financially and in the potential delay in changing to a more effective treatment.

Tumor response assessment by measuring the single largest lesion per organ in advanced non-small cell lung cancer patients treated with PD-1/PD-L1 inhibitor.

Background: For Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST1.1), measuring up to two target lesions per organ is an arbitrary criterion. Objectives: We sought to compare response assessment using RECIST1.1 and modified RECIST1.1 (mRECIST1.1, measuring the single largest lesion per organ) in advanced non-small cell lung cancer (aNSCLC) patients undergoing anti-PD-1/PD-L1 monotherapy. Methods: Concordance of radiologic response categorization between RECIST1.1 and mRECIST1.1 was compared using the Kappa statistics. C-index was calculated to evaluate prognostic accuracy of radiologic response by the two criteria. The Kaplan-Meier method and Cox regression analysis were conducted for progression-free survival (PFS) and overall survival (OS). Results: Eighty-seven patients who had at least two target lesions in any organ per the RECIST1.1 were eligible for comparison analysis. Tumor response showed excellent concordance when measured using the RECIST1.1 and mRECIST1.1 (Kappa = 0.961). C-index by these two criteria was similar for PFS (0.784 versus 0.785) and OS (0.649 versus 0.652). Responders had significantly longer PFS and OS versus non-responders (p < 0.05), whichever criterion adopted. Radiologic response remained a significant predictor of PFS and OS in multivariate analysis (p < 0.05). Conclusion: The mRECIST1.1 was comparable to RECIST1.1 in response assessment among aNSCLC patients who received single-agent PD-1/PD-L1 inhibitor. The mRECIST1.1, with reduced number of lesions to be measured, may be sufficient and more convenient to assess antitumor activity in clinical practice.

Kappa statistic considerations in evaluating inter-rater reliability between two raters: which, when and context matters.

BACKGROUND: In research designs that rely on observational ratings provided by two raters, assessing inter-rater reliability (IRR) is a frequently required task. However, some studies fall short in properly utilizing statistical procedures, omitting essential information necessary for interpreting their findings, or inadequately addressing the impact of IRR on subsequent analyses' statistical power for hypothesis testing. METHODS: This article delves into the recent publication by Liu et al. in BMC Cancer, analyzing the controversy surrounding the Kappa statistic and methodological issues concerning the assessment of IRR. The primary focus is on the appropriate selection of Kappa statistics, as well as the computation, interpretation, and reporting of two frequently used IRR statistics when there are two raters involved. RESULTS: The Cohen's Kappa statistic is typically utilized to assess the level of agreement between two raters when there are two categories or for unordered categorical variables with three or more categories. On the other hand, when it comes to evaluating the degree of agreement between two raters for ordered categorical variables comprising three or more categories, the weighted Kappa is a widely used measure. CONCLUSION: Despite not substantially affecting the findings of Liu et al.?s study, the statistical dispute underscores the significance of employing suitable statistical methods. Rigorous and accurate statistical results are crucial for producing trustworthy research.

German specialists treating testicular cancer follow different guidelines with resulting inconsistency in assessment of retroperitoneal lymph-node metastasis: clinical implications and possible corrective measures.

BACKGROUND: Testicular germ cell tumors (GCTs) are aggressive but highly curable tumors. To avoid over/undertreatment, reliable clinical staging of retroperitoneal lymph-node metastasis is necessary. Current clinical guidelines, in their different versions, lack specific recommendations on how to measure lymph-node metastasis. OBJECTIVE: We aimed to assess the practice patterns of German institutions frequently treating testicular cancer for measuring retroperitoneal lymph-node size. METHODS: An 8-item survey was distributed among German university hospitals and members of the German Testicular Cancer Study Group. RESULTS: In the group of urologists, 54.7% assessed retroperitoneal lymph nodes depending on their short-axis diameter (SAD) (33.3% in any plane, 21.4% in the axial plane), while 45.3% used long-axis diameter (LAD) for the assessment (42.9% in any plane, 2.4% in the axial plane). Moreover, the oncologists mainly assessed lymph-node size based on the SAD (71.4%). Specifically, 42.9% of oncologists assessed the SAD in any plane, while 28.5% measured this dimension in the axial plane. Only 28.6% of oncologists considered the LAD (14.3% in any plane, 14.3% in the axial plane). None of the oncologists and 11.9% of the urologists (n = 5) always performed an MRI for the initial assessment, while for follow-up imaging, the use increased to 36.5% of oncologists and 31% of urologists. Furthermore, only 17% of the urologists, and no oncologists, calculated lymph-node volume in their assessment (p = 0.224). CONCLUSION: Clear and consistent measurement instructions are urgently needed to be present in all guidelines across different specialistic fields involved in testicular cancer management.

Immunotherapy Assessment: A New Paradigm for Radiologists.

Immunotherapy denotes an exemplar change in an oncological setting. Despite the effective application of these treatments across a broad range of tumors, only a minority of patients have beneficial effects. The efficacy of immunotherapy is affected by several factors, including human immunity, which is strongly correlated to genetic features, such as intra-tumor heterogeneity. Classic imaging assessment, based on computed tomography (CT) or magnetic resonance imaging (MRI), which is useful for conventional treatments, has a limited role in immunotherapy. The reason is due to different patterns of response and/or progression during this kind of treatment which differs from those seen during other treatments, such as the possibility to assess the wide spectrum of immunotherapy-correlated toxic effects (ir-AEs) as soon as possible. In addition, considering the unusual response patterns, the limits of conventional response criteria and the necessity of using related immune-response criteria are clear. Radiomics analysis is a recent field of great interest in a radiological setting and recently it has grown the idea that we could identify patients who will be fit for this treatment or who will develop ir-AEs.

Automatic segmentation of hepatic metastases on DWI images based on a deep learning method: assessment of tumor treatment response according to the RECIST 1.1 criteria.

BACKGROUND: Evaluation of treated tumors according to Response Evaluation Criteria in Solid Tumors (RECIST) criteria is an important but time-consuming task in medical imaging. Deep learning methods are expected to automate the evaluation process and improve the efficiency of imaging interpretation. OBJECTIVE: To develop an automated algorithm for segmentation of liver metastases based on a deep learning method and assess its efficacy for treatment response assessment according to the RECIST 1.1 criteria. METHODS: One hundred and sixteen treated patients with clinically confirmed liver metastases were enrolled. All patients had baseline and post-treatment MR images. They were divided into an initial (n = 86) and validation cohort (n = 30) according to the examined time. The metastatic foci on DWI images were annotated by two researchers in consensus. Then the treatment responses were assessed by the two researchers according to RECIST 1.1 criteria. A 3D U-Net algorithm was trained for automated liver metastases segmentation using the initial cohort. Based on the segmentation of liver metastases, the treatment response was assessed automatically with a rule-based program according to the RECIST 1.1 criteria. The segmentation performance was evaluated using the Dice similarity coefficient (DSC), volumetric similarity (VS), and Hausdorff distance (HD). The area under the curve (AUC) and Kappa statistics were used to assess the accuracy and consistency of the treatment response assessment by the deep learning model and compared with two radiologists [attending radiologist (R1) and fellow radiologist (R2)] in the validation cohort. RESULTS: In the validation cohort, the mean DSC, VS, and HD were 0.85 ± 0.08, 0.89 ± 0.09, and 25.53 ± 12.11 mm for the liver metastases segmentation. The accuracies of R1, R2 and automated segmentation-based assessment were 0.77, 0.65, and 0.74, respectively, and the AUC values were 0.81, 0.73, and 0.83, respectively. The consistency of treatment response assessment based on automated segmentation and manual annotation was moderate [K value: 0.60 (0.34-0.84)]. CONCLUSION: The deep learning-based liver metastases segmentation was capable of evaluating treatment response according to RECIST 1.1 criteria, with comparable results to the junior radiologist and superior to that of the fellow radiologist.

The Evolving Scenario in the Assessment of Radiological Response for Hepatocellular Carcinoma in the Era of Immunotherapy: Strengths and Weaknesses of Surrogate Endpoints.

Hepatocellular carcinoma (HCC) is a challenging malignancy characterised by clinical and biological heterogeneity, independent of the stage. Despite the application of surveillance programs, a substantial proportion of patients are diagnosed at advanced stages when curative treatments are no longer available. The landscape of systemic therapies has been rapidly growing over the last decade, and the advent of immune-checkpoint inhibitors (ICIs) has changed the paradigm of systemic treatments. The coexistence of the tumour with underlying cirrhosis exposes patients with HCC to competing events related to tumour progression and/or hepatic decompensation. Therefore, it is relevant to adopt proper clinical endpoints to assess the extent of treatment benefit. While overall survival (OS) is the most accepted endpoint for phase III randomised controlled trials (RCTs) and drug approval, it is affected by many limitations. To overcome these limits, several clinical and radiological outcomes have been used. For instance, progression-free survival (PFS) is a useful endpoint to evaluate the benefit of sequential treatments, since it is not influenced by post-progression treatments, unlike OS. Moreover, radiological endpoints such as time to progression (TTP) and objective response rate (ORR) are frequently adopted. Nevertheless, the surrogacy between these endpoints and OS in the setting of unresectable HCC (uHCC) remains uncertain. Since most of the surrogate endpoints are radiology-based (e.g., PFS, TTP, ORR), the use of standardised tools is crucial for the evaluation of radiological response. The optimal way to assess the radiological response has been widely debated, and many criteria have been proposed over the years. Furthermore, none of the criteria have been validated for immunotherapy in advanced HCC. The coexistence of the underlying chronic liver disease and the access to several lines of treatments highlight the urgent need to capture early clinical benefit and the need for standardised radiological criteria to assess cancer response when using ICIs in mono- or combination therapies. Here, we review the most commonly used clinical and radiological endpoints for trial design, as well as their surrogacy with OS. We also review the criteria for radiological response to treatments for HCC, analysing the major issues and the potential future perspectives.

The α-RECIST (RECIST 1.1 Combined With Alpha Fetoprotein): A Novel Tool for Identifying Tumor Response of Conversion-Radiotherapy for Unresectable Hepatocellular Carcinoma Before Hepatectomy.

Purpose: To develop a novel criterion based on the response evaluation criteria in solid tumors (RECIST) 1.1 and alpha fetoprotein (AFP) and evaluate its performance in tumor response for patients with unresectable hepatocellular carcinoma (uHCC) receiving conversion-radiotherapy before hepatectomy. Method: From June 2012 to December 2020, a total of 39 patients with uHCC, who received intensity-modulated radiotherapy (IMRT) before hepatectomy, were retrospectively included in this study. Pre- and post-treatment contrast-enhanced magnetic resonance imaging (CE-MRI) scans were performed in all patients. Eight modified criteria were developed with the combination of RECIST 1.1, modified RECIST (mRECIST), and the percentage change of AFP, baseline AFP. The endpoint events were recurrence-free survival (RFS). Results: The median RFS and OS was 26.5 (IQR, 15.7-43.1), 38.8 (IQR, 18.4-53.6) months. An optimal revised evaluation criterion named α-RECIST (alpha fetoprotein-RECIST 1.1) was developed by combining the RECIST 1.1 with the AFPΔ (cut-off value, 76%). Patients defined as responders by α-RECIST showed significantly better RFS and OS than those defined as non-responders (p = 0.035, 0.048). The other criteria (RECIST 1.1, mRECIST, αΔ-mRECIST, α&Δ-RECIST, α&Δ-mRECIST, αBL-RECIST, αBL-mRECIST, α&BL-RECIST, α&BL-mRECIST) all failed to identify responders from non-responders (p = 0.405, 0.201, 0.773, 0.424, 0.266, 0.060, 0.721, 0.644, 0.910, respectively) when correlated with RFS. Responders according to α-RECIST showed significant better RFS compared to non-responders [HR, 0.31 (95% CI: 0.10, 0.98); p=0.046], but no statistical significance was observed in terms of OS [HR, 0.33 (95% CI: 0.11, 1.05); p = 0.06]. Conclusions: Patients identified as responders by α-RECIST provided significant better RFS. The α-RECIST criteria might be a promising tool for identifying tumor response of conversion-radiotherapy for unresectable hepatocellular carcinoma before hepatectomy.

Continuation of Lorlatinib in ALK-Positive NSCLC Beyond Progressive Disease.

INTRODUCTION: Lorlatinib, a potent, selective third-generation ALK tyrosine kinase inhibitor (TKI), exhibited overall and intracranial antitumor activity in patients with ALK-positive NSCLC. METHODS: Retrospective analyses in the ongoing phase 2 trial (NCT01970865) investigated the clinical benefit of continuing lorlatinib beyond progressive disease (LBPD). Patients with previous crizotinib treatment as the only ALK TKI were group A (n = 28); those with at least one previous second-generation ALK TKIs were group B (n = 74). LBPD was defined as greater than 3 weeks of lorlatinib treatment after investigator-assessed progressive disease. Only patients with the best overall response of complete or partial response or stable disease were included. RESULTS: There were no major differences in baseline characteristics between groups. The median duration of treatment for patients who continued LBPD was 32.4 months (group A) and 16.4 months (group B) versus 12.5 months (group A) and 7.7 months (group B) for patients who did not continue LBPD. The median overall survival in group A was not reached (NR) in patients who continued LBPD versus 24.4 months (95% confidence interval [CI]: 12.1-NR); group B's median was 26.5 months (95% CI: 18.7-35.5) in patients who continued LBPD versus 14.7 months (95% CI: 9.3-38.5) in patients who did not continue LBPD. The median overall survival postprogression for groups A and B was NR (95% CI: 21.4-NR) and 14.6 months (95% CI: 11.2-19.2) in patients who continued LBPD and 8.0 months (95% CI: 1.5-NR) versus 5.3 months (95% CI: 2.8-14.3) in patients who did not continue LBPD. CONCLUSIONS: Continuing LBPD is a viable treatment strategy for select patients with ALK-positive NSCLC who progressed on lorlatinib.

Assessment of immunotherapy response in intracranial malignancy using semi-automatic segmentation on magnetic resonance images.

Objective: To explore multi-aspect radiologic assessment of immunotherapy response in intracranial malignancies based on a semi-automatic segmentation technique, and to explore volumetric thresholds with good performance according to RECIST 1.1 thresholds. Methods: Patients diagnosed with intracranial malignancies and treated with immunotherapy were included retrospectively. In all MR images, target lesions were measured using a semi-automatic segmentation technique that could intelligently generate visual diagrams including RECIST 1.1, total volume, and max. 3D diameter. The changes in parameters were calculated for each patient after immunotherapy. The ROC curve was used to analyze the sensitivity and specificity of the size change of the legion. This was useful to find new volumetric thresholds with better efficiency in response assessment. The changes in total volume were assessed by conventional volumetric thresholds, while RECIST 1.1 thresholds were for the max. 3D diameter. A chi-square test was used to compare the concordance and diagnostic correlation between the response assessment results of the three criteria. Results: A total of 20 cases (average age, 58 years; range, 23 to 84 years) and 58 follow-up MR examinations after immunotherapy were included in the analysis. The P-value of the chi-square test between RECIST 1.1 and total volume is 0 (P <0.05), same as that in RECIST 1.1 and max. 3D diameter. The kappa value of the former two was 0.775, and the kappa value for the latter two was 0.742. The above results indicate a significant correlation and good concordance for all three criteria. In addition, we also found that the volumetric assessment had the best sensitivity and specificity for the immunotherapy response in intracranial malignancies, with a PR threshold of -64.9% and a PD threshold of 21.4%. Conclusions: Radiologic assessment of immunotherapy response in intracranial malignancy can be performed by multiple criteria based on semi-automatic segmentation technique on MR images, such as total volume, max. 3D diameter and RECIST 1.1. In addition, new volumetric thresholds with good sensitivity and specificity were found by volumetric assessment.