The Value of 18F-FDG PET/CT in Predicting the Response to PD-1 Blocking Immunotherapy in Advanced NSCLC Patients with High-Level PD-L1 Expression

Vekens, K; Everaert, Hendrik; Neyns, Bart; Ilsen, Bart; Decoster, Lore

doi:10.1016/j.cllc.2021.03.001

Cited by 18 publications

(24 citation statements)

References 22 publications

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“…Four studies were conducted in France ( 20 , 22 , 26 , 27 ), followed by three in Italy ( 16 , 18 , 21 ) and three in Japan ( 16 , 18 , 21 ). We also identified a single study in the United States ( 19 ), Israel ( 24 ) and Belgium ( 28 ). Two studies were of a prospective design ( 18 , 20 ).…”

Section: Resultsmentioning

confidence: 99%

“…Two studies were of a prospective design ( 18 , 20 ). SUV, MTV and TLG were measured in four studies ( 18 , 20 , 25 , 28 ) and MTV alone was measured in five studies ( 17 , 19 , 21 , 22 , 24 ).…”

Section: Resultsmentioning

confidence: 99%

“…Regarding types of ICIs, nine studies ( 17 , 20 – 25 , 27 , 28 ) reported using PD-1 inhibitors, while three used PD-1 and PD-L1 inhibitors ( 16 , 18 , 26 ). Patients were divided into high or low SUV/MTV/TLG groups in each study based on the cut-off values, and their PFS/OS were analyzed.…”

Section: Resultsmentioning

confidence: 99%

“…All of them classified responses to ICIs as complete remission (CR), partial response (PR), stable disease (SD), and progression of disease (PD) based on the Response Evaluation Criteria In Solid Tumors (RECIST) 1.1. Four articles demonstrated that none of the PET/CT parameters significantly correlated with ICIs response ( 17 , 23 , 28 , 29 ). However, the other four studies showed that NSCLC patients who achieved CR, PR, or SD after ICIs treatment had significantly lower median MTV values than those with PD ( 16 , 26 , 27 , 30 ).…”

Section: Resultsmentioning

confidence: 99%

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Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

Zhu

Wang

et al. 2022

Front. Oncol.

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BackgroundImmune checkpoint inhibitors (ICIs) have emerged as a promising treatment option for advanced non-small-cell lung cancer (NSCLC) patients, highlighting the need for biomarkers to identify responders and predict the outcome of ICIs. The purpose of this study was to evaluate the predictive value of baseline standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) derived from 18F-FDG-PET/CT in advanced NSCLC patients receiving ICIs.MethodsPubMed and Web of Science databases were searched from January 1st, 2011 to July 18th, 2022, utilizing the search terms “non-small-cell lung cancer”, “PET/CT”, “standardized uptake value”, “metabolic tumor volume”, “ total lesion glycolysis”, and “immune checkpoint inhibitors”. Studies that analyzed the association between PET/CT parameters and objective response, immune-related adverse events (irAEs) and prognosis of NSCLC patients treated with ICIs were included. We extracted the hazard ratio (HR) with a 95% confidence interval (CI) for progression-free survival (PFS) and overall survival (OS). We performed a meta-analysis of HR using Review Manager v.5.4.1.ResultsSixteen studies were included for review and thirteen for meta-analysis covering 770 patients. As for objective response and irAEs after ICIs, more studies with consistent assessment methods are needed to determine their relationship with MTV. In the meta-analysis, low SUVmax corresponded to poor PFS with a pooled HR of 0.74 (95% CI, 0.57-0.96, P=0.02). And a high level of baseline MTV level was related to shorter PFS (HR=1.45, 95% CI, 1.11-1.89, P<0.01) and OS (HR, 2.72; 95% CI, 1.97-3.73, P<0.01) especially when the cut-off value was set between 50-100 cm3. SUVmean and TLG were not associated with the prognosis of NSCLC patients receiving ICIs.ConclusionsHigh level of baseline MTV corresponded to shorter PFS and OS, especially when the cut-off value was set between 50-100 cm3. MTV is a potential predictive value for the outcome of ICIs in NSCLC patients.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 2 more Smart Citations

Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

Zhu

Wang

et al. 2022

Front. Oncol.

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“…To date, special attention has been given to other parameters obtainable from [ 18 F]FDG PET/CT during ICI. Not just standardized uptake value (SUV), but also metabolic tumor volume (MTV) and total lesion glycolysis (TLG), have been investigated at baseline and during treatment as absolute values or as variations to predict response and outcome [ 28 , 47 , 51 , 53 , 54 , 55 , 56 , 58 , 59 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 76 , 77 , 78 , 79 , 82 , 83 , 86 , 87 , 88 ]. While SUV appears to be inversely correlated to response to ICI [ 66 , 70 , 80 ] with higher SUV values being in some reports indicative of treatment benefit, on the other hand higher MTV and TLG values result in negative predictive factors for patient outcome during ICI ( Table 2 ).…”

Section: Combined Parameters For Outcome Predictionmentioning

confidence: 99%

Immunotherapy Monitoring with Immune Checkpoint Inhibitors Based on [18F]FDG PET/CT in Metastatic Melanomas and Lung Cancer

Lopci

2021

JCM

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Immunotherapy with checkpoint inhibitors has prompted a major change not only in cancer treatment but also in medical imaging. In parallel with the implementation of new drugs modulating the immune system, new response criteria have been developed, aiming to overcome clinical drawbacks related to the new, unusual, patterns of response characterizing both solid tumors and lymphoma during the course of immunotherapy. The acknowledgement of pseudo-progression, hyper-progression, immune-dissociated response and so forth, has become mandatory for all imagers dealing with this clinical scenario. A long list of acronyms, i.e., irRC, iRECIST, irRECIST, imRECIST, PECRIT, PERCIMT, imPERCIST, iPERCIST, depicts the enormous effort made by radiology and nuclear medicine physicians in the last decade to optimize imaging parameters for better prediction of clinical benefit in immunotherapy regimens. Quite frequently, a combination of clinical-laboratory data with imaging findings has been tested, proving the ability to stratify patients into various risk groups. The next steps necessarily require a large scale validation of the most robust criteria, as well as the clinical implementation of immune-targeting tracers for immuno-PET or the exploitation of radiomics and artificial intelligence as complementary tools during the course of immunotherapy administration. For the present review article, a summary of PET/CT role for immunotherapy monitoring will be provided. By scrolling into various cancer types and applied response criteria, the reader will obtain necessary information for better understanding the potentials and limitations of the modality in the clinical setting.

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Patlak-Ki derived from ultra-high sensitivity dynamic total body [18F]FDG PET/CT correlates with the response to induction immuno-chemotherapy in locally advanced non-small cell lung cancer patients

Wang,

Qiu,

Liu

et al. 2023

Eur J Nucl Med Mol Imaging

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The Value of 18F-FDG PET/CT in Predicting the Response to PD-1 Blocking Immunotherapy in Advanced NSCLC Patients with High-Level PD-L1 Expression

Cited by 18 publications

References 22 publications

Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

Predictive value of baseline metabolic tumor volume for non-small-cell lung cancer patients treated with immune checkpoint inhibitors: A meta-analysis

Immunotherapy Monitoring with Immune Checkpoint Inhibitors Based on [18F]FDG PET/CT in Metastatic Melanomas and Lung Cancer

Patlak-Ki derived from ultra-high sensitivity dynamic total body [18F]FDG PET/CT correlates with the response to induction immuno-chemotherapy in locally advanced non-small cell lung cancer patients

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