Dynamic alteration in SULmax predicts early pathological tumor response and short-term prognosis in non-small cell lung cancer treated with neoadjuvant immunochemotherapy

The utility of 18F-FDG PET/CT for predicting the pathological response and prognosis to neoadjuvant immunochemotherapy in resectable non-small-cell lung cancer

OBJECTIVE

To evaluate the potential utility of 18F-FDG PET/CT to assess response to neoadjuvant immunochemotherapy in patients with resectable NSCLC, and the ability to screen patients who may benefit from neoadjuvant immunochemotherapy.

METHODS

Fifty one resectable NSCLC (stage IA-IIIB) patients were analyzed, who received two-three cycles neoadjuvant immunochemotherapy.18F-FDG PET/CT was carried out at baseline(scan-1) and prior to radical resection(scan-2). SULmax, SULpeak, MTV, TLG, T/N ratio, ΔSULmax%,ΔSULpeak%, ΔMTV%, ΔTLG%,ΔT/N ratio% were calculated. 18F-FDG PET/CT responses were classified using PERCIST. We then compared the RECIST 1.1 and PERCIST criteria for response assessment.With surgical pathology of primary lesions as the gold standard, the correlation between metabolic parameters of 18F-FDG PET/CT and major pathologic response (MPR) was analyzed. All metabolic parameters were compared to treatment response and correlated to PFS and OS.

RESULTS

In total of fifty one patients, MPR was achieved in 25(49%, 25/51) patients after neoadjuvant therapy. The metabolic parameters of Scan-1 were not correlated with MPR.The degree of pathological regression was negatively correlated with SULmax, SULpeak, MTV, TLG, T/N ratio of scan-2, and the percentage changes of the ΔSULmax%, ΔSULpeak%, ΔMTV%,ΔTLG%,ΔT/N ratio% after neoadjuvant therapy (p < 0.05). According to PERCIST, 36 patients (70.6%, 36/51) showed PMR, 12 patients(23.5%, 12/51) had stable metabolic disease(SMD), and 3 patients(5.9%, 3/51) had progressive metabolic disease (PMD). ROC indicated that all of scan-2 metabolic parameters and the percentage changes of metabolic parameters had ability to predict MPR and non-MPR, SULmax and T/N ratio of scan-2 had the best differentiation ability.The accuracy of RECIST 1.1 and PERCIST criteria were no statistical significance(p = 0.91). On univariate analysis, ΔMTV% has the highest correlation with PFS.

CONCLUSIONS

Metabolic response by 18F-FDG PET/CT can predict MPR to neoadjuvant immunochemotherapy in resectable NSCLC. ΔMTV% was significantly correlated with PFS.

Easily applicable predictive score for MPR based on parameters before neoadjuvant chemoimmunotherapy in operable NSCLC: a single-center, ambispective, observational study

BACKGROUND

Neoadjuvant chemoimmunotherapy (NACI) is promising for resectable nonsmall cell lung cancer (NSCLC), but predictive biomarkers are still lacking. The authors aimed to develop a model based on pretreatment parameters to predict major pathological response (MPR) for such an approach.

METHODS

The authors enrolled operable NSCLC treated with NACI between March 2020 and May 2023 and then collected baseline clinical-pathology data and routine laboratory examinations before treatment. The efficacy and safety data of this cohort was reported and variables were screened by Logistic and Lasso regression and nomogram was developed. In addition, receiver operating characteristic curves, calibration curves, and decision curve analysis were used to assess its power. Finally, internal cross-validation and external validation was performed to assess the power of the model.

RESULTS

In total, 206 eligible patients were recruited in this study and 53.4% (110/206) patients achieved MPR. Using multivariate analysis, the predictive model was constructed by seven variables, prothrombin time (PT), neutrophil percentage (NEUT%), large platelet ratio (P-LCR), eosinophil percentage (EOS%), smoking, pathological type, and programmed death ligand-1 (PD-L1) expression finally. The model had good discrimination, with area under the receiver operating characteristic curve (AUC) of 0.775, 0.746, and 0.835 for all datasets, cross-validation, and external validation, respectively. The calibration curves showed good consistency, and decision curve analysis indicated its potential value in clinical practice.

CONCLUSION

This real world study revealed favorable efficacy in operable NSCLC treated with NACI. The proposed model based on multiple clinically accessible parameters could effectively predict MPR probability and could be a powerful tool in personalized medication.

Utility of 18F-FDG PET/CT uptake values in predicting response to neoadjuvant chemoimmunotherapy in resectable non-small cell lung cancer

INTRODUCTION

Reliable predictive markers are lacking for resectable non-small cell lung cancer (NSCLC) patients treated with neoadjuvant chemoimmunotherapy. The present study investigated the utility of SUV_max values acquired from PET/CT to predict the response to neoadjuvant chemoimmunotherapy for resectable NSCLC.

MATERAL AND METHODS

SUV_max, clinical and pathological outcomes, were collected from patients in 5 hospitals. Patients who received dynamic PET/CT surveillance were divided into cohorts A (chemoimmunotherapy) and B (chemotherapy), respectively, while cohort C (chemoimmunotherapy) comprised patients undergoing post-therapy PET/CT. Associations between SUV_max and major pathologic response (MPR) were evaluated through receiver operating characteristic (ROC) curves.

RESULTS

A total of 129 cases with an MPR rate of 46.5 % was identified. In neoadjuvant chemoimmunotherapy, ΔSUV_max% (AUC: 0.890, 95 % CI: 0.761-0.949) and post-therapy SUV_max (AUC: 0.933, 95 % CI: 0.802-0.959) could accurately predict MPR. On the contrary, the baseline SUV_max was not associated with MPR (p = 0.184). Furthermore, an independent cohort C proved that post-therapy SUV_max could serve as an independent predictor (AUC: 0.928, 95 % CI: 0.823-0.958). In addition, robust predictive performance could be observed when we use the optimal cut-off point of both ΔSUV_max% (54.4 %, AUC: 0.912, 95 % CI: 0.824-0.994) and post-therapy SUV_max (3.565, AUC: 0.912, 95 % CI: 0.824-0.994) in neoadjuvant chemoimmunotherapy. The RNA data revealed that the expression of PFKFB4, a key enzyme in glycolysis, was positively correlated with SUV_max value and tumor cell proliferation after neoadjuvant chemoimmunotherapy.

CONCLUSION

These findings highlighted that the ΔSUV_max% and remained SUV_max were accurate and non-invasive tests for the prediction of MPR after neoadjuvant chemoimmunotherapy.