Comprehensive Clinical and Genetic Characterization of Hyperprogression Based on Volumetry in Advanced Non–Small Cell Lung Cancer Treated With Immune Checkpoint Inhibitor

Kim, Youjin; Kim, Chu Hyun; Lee, Ho Yun; Lee, Se‐Hoon; Kim, Hong Sook; Lee, Sook; Cha, Hongui; Hong, Sungchul; Kim, Kyunga; Seo, Sang Won; Sun, Jong‐Mu; Ahn, Myung‐Ju; Ahn, Jin Seok; Park, Keunchil

doi:10.1016/j.jtho.2019.05.033

Cited by 79 publications

(105 citation statements)

References 19 publications

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“…NLR has been studied in patients treated with ICIs in different types of cancers and several thresholds have been proposed [47][48][49]. Higher derived NLR was associated with poor survival outcome [50] and hyperprogressive disease [51] in NSCLC patients treated with ICIs. A meta-analysis including 14 retrospective analyses and 1225 patients suggested that NLR may have a prognostic role in NSCLC patients receiving nivolumab [52].…”

Section: Discussionmentioning

confidence: 99%

EPSILoN: A Prognostic Score for Immunotherapy in Advanced Non-Small-Cell Lung Cancer: A Validation Cohort

Prelaj

Ferrara

Rebuzzi

et al. 2019

Cancers

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Background: Beyond programmed death ligand 1 (PD-L1), no other biomarkers for immunotherapy are used in daily practice. We previously created EPSILoN (Eastern Cooperative Oncology Group performance status (ECOG PS), smoking, liver metastases, lactate dehydrogenase (LDH), neutrophil-to-lymphocyte ratio (NLR)) score, a clinical/biochemical prognostic score, in 154 patients treated with second/further-line immunotherapy. This study’s aim was to validate EPSILoN score in a different population group. Methods: 193 patients were included at National Cancer Institute of Milan (second-line immunotherapy, 61%; further-line immunotherapy, 39%). Clinical/laboratory parameters such as neutrophil-to-lymphocyte ratio and lactate dehydrogenase levels were collected. Kaplan–Meier and Cox hazard methods were used for survival analysis. Results: Overall median progression-free survival and median overall survival were 2.3 and 7.6 months, respectively. Multivariate analyses for Progression-Free Survival (PFS) identified heavy smokers (hazard ratio (HR) 0.71, p = 0.036) and baseline LDH < 400 mg/dL (HR 0.66, p = 0.026) as independent positive factors and liver metastases (HR 1.48, p = 0.04) and NLR ≥ 4 (HR 1.49, p = 0.029) as negative prognostic factors. These five factors were included in the EPSILoN score which was able to stratify patients in three different prognostic groups, high, intermediate and low, with PFS of 6.0, 3.8 and 1.9 months, respectively (HR 1.94, p < 0.001); high, intermediate and low prognostic groups had overall survival (OS) of 24.5, 8.9 and 3.4 months, respectively (HR 2.40, p < 0.001). Conclusions: EPSILoN, combining five baseline clinical/blood parameters (ECOG PS, smoking, liver metastases, LDH, NLR), may help to identify advanced non-small-cell lung cancer (aNSCLC) patients who most likely benefit from immune checkpoint inhibitors (ICIs).

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Section: Discussionmentioning

confidence: 99%

EPSILoN: A Prognostic Score for Immunotherapy in Advanced Non-Small-Cell Lung Cancer: A Validation Cohort

Prelaj

Ferrara

Rebuzzi

et al. 2019

Cancers

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“…The present study defined HPD based on the RECIST 1.1 criteria; however, because RECIST is a one-dimensional tumor assessment, a recent study suggested that a more accurate evaluation is possible by using volumetric measurement. 13 We found that age was significantly related to the development of HPD. The results of the correlation between age and HPD prevalence in previous studies are controversial.…”

Section: Discussionmentioning

confidence: 68%

Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors

Choi

Kim

et al. 2020

Thoracic Cancer

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Background: Hyperprogressive disease (HPD) is a paradoxical acceleration of tumor growth after immune checkpoint inhibitor (ICI) treatment. This study aimed to identify the risk factors and to present a predictive model for HPD in patients treated with ICIs. Methods: A total of 78 non-small cell lung cancer (NSCLC) cases, treated with at least two cycles of ICIs who underwent computed tomography (CT) for response assessment were recruited into the study from January 2016 to August 2019. HPD was defined by the following criteria: (i) time-to-treatment failure <2 months; (ii) a 50% increase in the sum of target lesion diameters; (iii) new development of at least two lesions in an already involved organ; (iv) appearance of a new organ lesion; and (v) a decrease in ECOG PS 2. Results: Of the 78 total patients, 15 (19.2%) had HPD. The risk factors of HPD were age; primary lesion size; and metastases in the contralateral lung, pleura, liver, and bone in multivariable logistic regression (odds ratio [OR]; 0.9038, 1.6619, 28.5913, 23.8264, 14.5711, and 20.1533, respectively, all P-values < 0.05). By using these risk factors, we developed a prediction model for HPD and the area under the receiver operating characteristic curve of the model was 0.9556 (95% confidence interval [CI]: 0.9133-0.9978). Conclusions: HPD is relatively common and associated with a grave clinical outcome, requiring a careful monitoring in lung cancer patients treated with ICIs. Moreover, risk factors such as age, size of tumor and number of various metastatic lesions should be taken into consideration before ICI administration.

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“…With ongoing research into resistance to checkpoint inhibitors and also hyperprogressive disease [54,55], there is potential for new biomarkers for response checkpoint inhibitors to be identified in the future.…”

Section: Data Gapsmentioning

confidence: 99%

Targeted literature review on use of tumor mutational burden status and programmed cell death ligand 1 expression to predict outcomes of checkpoint inhibitor treatment

Krieger¹,

Pearson²,

Bell³

et al. 2020

Diagn Pathol

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Background: To achieve optimal outcomes, an individual approach is needed in the treatment and care of patients. The potential value of tumor mutational burden (TMB) status and/or programmed cell death ligand 1 (PD-L1) expression as biomarkers to predict which patients are most likely to respond to checkpoint inhibitors has been explored in many studies. The goal of this targeted literature review is to identify data available for TMB status and/or PD-L1 expression that predict response to checkpoint inhibitors and/or anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) antibodies. Methods: Targeted literature searches were performed using electronic medical databases (MEDLINE, Embase, and BIOSIS) and internet searches of specified sites. Bibliographies of key systematic literature reviews and meta-analyses also were reviewed for studies of interest.Results: The review identified 27 studies of non-small cell lung cancer (NSCLC), 40 studies of melanoma, 10 studies of urothelial cancer, and 5 studies of renal cell cancer indications. Studies also were identified in other cancer types, e.g., colorectal, breast, gastric, and Merkel cell cancer and squamous-cell carcinoma of the head and neck. Twelve trials, including six in NSCLC and four in melanoma, evaluated TMB as a predictor of outcomes. A TMB of ≥10 mutations per megabase was shown to be an effective biomarker in the CheckMate 227 study. PD-L1 expression was included in the majority of identified studies and was found to predict response in in melanoma and in all types of NSCLC. Prediction of response was not a prespecified analysis in some studies; others had small sample sizes and wide confidence intervals. A clear predictive trend for PD-L1 expression was not identified in renal, breast, gastric, or Merkel cell cancer.Conclusion: Based on data contained in this review, assessment of TMB status and PD-L1 expression may help enhance the prediction of response to checkpoint inhibition in some tumors, such as NSCLC and melanoma. In this rapidly growing area of research, further exploratory biomarkers are being investigated including tumor-infiltrating lymphocytes, immune profiling (e.g., effector T cells or regulatory T cells), epigenetic signatures, T-cell receptor repertoire, proteomics, microbiome, and metabolomics.

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Comprehensive Clinical and Genetic Characterization of Hyperprogression Based on Volumetry in Advanced Non–Small Cell Lung Cancer Treated With Immune Checkpoint Inhibitor

Cited by 79 publications

References 19 publications

EPSILoN: A Prognostic Score for Immunotherapy in Advanced Non-Small-Cell Lung Cancer: A Validation Cohort

EPSILoN: A Prognostic Score for Immunotherapy in Advanced Non-Small-Cell Lung Cancer: A Validation Cohort

Prediction model for hyperprogressive disease in non‐small cell lung cancer treated with immune checkpoint inhibitors

Targeted literature review on use of tumor mutational burden status and programmed cell death ligand 1 expression to predict outcomes of checkpoint inhibitor treatment

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