Clinical factors and major pathological response after neoadjuvant chemoimmunotherapy in potentially resectable lung squamous cell carcinoma

Objective

Major pathological response (MPR) helps evaluate the prognosis of patients with lung squamous cell carcinoma (LUSC). However, the clinical factors that affect the achievement of MPR after neoadjuvant chemoimmunotherapy (NCIO) in patients with LUSC remain unclear. This study aimed to explore the clinical factors affecting the MPR after NCIO in patients with potentially resectable LUSC.

Methods

This retrospective study included patients with stage IIB-IIIC LUSC who underwent surgical resection after receiving NCIO at a center between March 2020 and November 2022. In addition to the postoperative pathological remission rate, sex, age, body mass index (BMI), smoking history, TNM stage, hematological and imaging test results, and other indicators were examined before NCIO. According to the pathological response rate of the surgically removed tumor tissue, the patients were split into MPR and non-MPR groups.

Results

In total, 91 LUSC patients who met the study's eligibility criteria were enrolled: 32 (35%) patients in the non-MPR group and 59 (65%) in the MPR group, which included 43 cases of pathological complete remission (pCR). Pre-treatment lymphocyte level (LY) (odds ratio [OR] =5.997), tumor burden (OR=0.958), N classification (OR=15.915), radiographic response (OR=11.590), pulmonary atelectasis (OR=5.413), and PD-L1 expression (OR=1.028) were independently associated with MPR (all P < 0.05). Based on these six independent predictors, we developed a nomogram model of prediction having an area under the curve (AUC) of 0.914 that is simple to apply clinically to predict the MPR. The MPR group showed greater disease-free survival (DFS) than the non-MPR group, according to the survival analysis (P < 0.001).

Conclusion

The MPR rate of NCIO for potentially resectable LUSC was 65%. LY, tumor burden, N classification, radiographic response, pulmonary atelectasis, and PD-L1 expression in patients with LUSC before NCIO were the independent and ideal predictors of MPR. The developed nomogram demonstrated a good degree of accuracy and resilience in predicting the MPR following NCIO, indicating that it is a useful tool for assuring customized therapy for patients with possibly resectable LUSC.

Efficacy, safety, and correlative biomarkers of bintrafusp alfa in recurrent or metastatic nasopharyngeal cancer patients: a phase II clinical trial

Background

The strategy of dual blockade of TGF-β and PD-L1 pathways has not been previously tested in platinum-refractory recurrent or metastatic nasopharyngeal cancer (R/M NPC) patients. This study aimed to evaluate the safety and efficacy of bintrafusp alfa in refractory R/M NPC patients.

Methods

In this single-arm, single-centre phase II clinical trial, 38 histologically confirmed R/M NPC patients were enrolled and administered with bintrafusp alfa every 2 weeks. Primary endpoint was objective response rate (ORR) per Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1). Secondary endpoints included progression-free survival (PFS), overall survival (OS), duration of response (DOR), and safety.

Findings

Thirty-eight patients were accrued (33 men; median age, 54 years). ORR was 23.7% (complete response, n = 2; partial response, n = 7). The median DOR was 19.2 months, median PFS was 2.3 months, median OS was 17.0 months, and 1-year OS rate was 63.2%. Unfortunately, 25 patients (65.7%) progressed within 8 weeks of treatment, 15 patients (39.5%) and 8 patients (21.1%) developed hyper-progressive disease (HPD) per RECIST v1.1 and tumor growth rate (TGR) ratio respectively. Sixteen patients (42.4%) experienced ≥ grade 3 treatment-related adverse events (TRAEs), most commonly anemia (n = 9, 23.7%) and secondary malignancies (n = 4, 10.5%). TRAEs led to permanent treatment discontinuation in 7 patients. Patients with strong suppression of plasma TGFβ1 level at week 8 were unexpectedly associated with worse ORR (9.1% vs 44.4%, P = 0.046) and development of HPD. There was no correlation between PD-L1 expression and ORR.

Interpretation

Bintrafusp alfa demonstrated modest activity in R/M NPC but high rates of HPD and treatment discontinuation secondary to TRAEs are concerning.

Funding

The project was supported by Alice Ho Miu Ling Nethersole Charity Foundation Professorship Endowed Fund and Merck KGaA.

Dosimetric Effect of Thymus and Thoracic Duct on Radiation-Induced Lymphopenia in Patients With Primary Lung Cancer Who Received Thoracic Radiation

Purpose

Radiation-induced lymphopenia is a well-recognized factor for tumor control and survival in patients with cancer. This study aimed to determine the role of radiation dose to the thymus and thoracic duct on radiation-induced lymphopenia.

Methods and Materials

Patients with primary lung cancer treated with thoracic radiation therapy between May 2015 and February 2020 with whole blood count data were eligible. Clinical characteristics, including age, gender, histology, stage, chemotherapy regimen, radiation dosimetry, and absolute lymphocyte count (ALC) were collected. The thymus and thoracic duct were contoured by one investigator for consistency and checked by one senior physician. The primary endpoint was radiation-induced decrease in lymphocytes, defined as the difference in ALC (DALC) before and after radiation therapy.

Results

The data of a total of 116 consecutive patients were retrospectively retrieved. Significant correlations were found between DALC and several clinical factors. These factors include stage, chemotherapy or concurrent chemoradiation, biologically effective dose (BED), mean lung dose, mean body dose, effective dose to immune cells (EDIC), mean thymus dose (MTD), and mean thoracic duct dose (MTDD) (all P < .05). Ridge regression showed that DALC = 0.0063 × BED + 0.0172 × EDIC + 0.0002 × MTD + 0.0147 × MTDD + 0.2510 (overall P = .00025 and F = 5.85). The combination model has the highest area under the curve of 0.77 (P < .001) when fitting the logistic regression model on DALC categorized as binary endpoint. The sensitivity and specificity of the combined model were 89% and 58%, respectively.

Conclusions

This study demonstrated for the first time that radiation doses to the thymus and thoracic duct are strongly associated with radiation-induced lymphopenia patients with lung cancer. Further validation studies are needed to implement thymus and thoracic duct as organs at risk.

The predictive role of soluble programmed death ligand 1 in digestive system cancers

Introduction

The prognostic role of soluble programmed death ligand 1 (sPD-L1) in digestive system cancers (DSCs) remains inconclusive. This study aimed to explore the predictive value of sPD-L1 expression in DSCs.

Methods

Comprehensive searches were run on the electronic databases (PubMed, Web of Science, EMBASE, and the Cochrane Library) to identify studies that assessed the prognostic role of sPD-L1 in DSCs. Review Manager software (version 5.3) was used for all analyses. Pooled data for survival outcomes were measured as hazard ratios (HRs), 95% confidence intervals (CIs), and odds ratios and their 95% CIs.

Results

The search identified 18 studies involving 2,070 patients with DSCs. The meta-outcome revealed that a high level of sPD-L1 was related to poorer overall survival (HR, 3.06; 95% CI: 2.22-4.22, p<0.001) and disease-free survival (HR, 2.53; 95% CI: 1.67-3.83, p<0.001) in DSCs. Individually, the prognostic significance of high level of sPD-L1 expression was the highest in hepatic cell carcinoma (HR, 4.76; p<0.001) followed by gastric cancer (HR=3.55, p<0.001).

Conclusion

sPD-L1 may be a prognostic factor in DSCs for overall survival and disease-free survival. Inflammatory cytokines, treatment approaches, and other factors may affect the expression of sPD-L1. Therefore, the prognostic value of sPD-L1 for recurrence and metastasis should be further investigated. sPD-L1 may also predict response to treatment. Well-designed prospective studies with standard assessment methods should be conducted to determine the prognostic value of sPD-L1 in DSCs.

Deep learning attention-guided radiomics for COVID-19 chest radiograph classification

Background

Accurate assessment of coronavirus disease 2019 (COVID-19) lung involvement through chest radiograph plays an important role in effective management of the infection. This study aims to develop a two-step feature merging method to integrate image features from deep learning and radiomics to differentiate COVID-19, non-COVID-19 pneumonia and normal chest radiographs (CXR).

Methods

In this study, a deformable convolutional neural network (deformable CNN) was developed and used as a feature extractor to obtain 1,024-dimensional deep learning latent representation (DLR) features. Then 1,069-dimensional radiomics features were extracted from the region of interest (ROI) guided by deformable CNN's attention. The two feature sets were concatenated to generate a merged feature set for classification. For comparative experiments, the same process has been applied to the DLR-only feature set for verifying the effectiveness of feature concatenation.

Results

Using the merged feature set resulted in an overall average accuracy of 91.0% for three-class classification, representing a statistically significant improvement of 0.6% compared to the DLR-only classification. The recall and precision of classification into the COVID-19 class were 0.926 and 0.976, respectively. The feature merging method was shown to significantly improve the classification performance as compared to using only deep learning features, regardless of choice of classifier (P value <0.0001). Three classes' F1-score were 0.892, 0.890, and 0.950 correspondingly (i.e., normal, non-COVID-19 pneumonia, COVID-19).

Conclusions

A two-step COVID-19 classification framework integrating information from both DLR and radiomics features (guided by deep learning attention mechanism) has been developed. The proposed feature merging method has been shown to improve the performance of chest radiograph classification as compared to the case of using only deep learning features.

Artificial intelligence-assisted multistrategy image enhancement of chest X-rays for COVID-19 classification

Background

The coronavirus disease 2019 (COVID-19) led to a dramatic increase in the number of cases of patients with pneumonia worldwide. In this study, we aimed to develop an AI-assisted multistrategy image enhancement technique for chest X-ray (CXR) images to improve the accuracy of COVID-19 classification.

Methods

Our new classification strategy consisted of 3 parts. First, the improved U-Net model with a variational encoder segmented the lung region in the CXR images processed by histogram equalization. Second, the residual net (ResNet) model with multidilated-rate convolution layers was used to suppress the bone signals in the 217 lung-only CXR images. A total of 80% of the available data were allocated for training and validation. The other 20% of the remaining data were used for testing. The enhanced CXR images containing only soft tissue information were obtained. Third, the neural network model with a residual cascade was used for the super-resolution reconstruction of low-resolution bone-suppressed CXR images. The training and testing data consisted of 1,200 and 100 CXR images, respectively. To evaluate the new strategy, improved visual geometry group (VGG)-16 and ResNet-18 models were used for the COVID-19 classification task of 2,767 CXR images. The accuracy of the multistrategy enhanced CXR images was verified through comparative experiments with various enhancement images. In terms of quantitative verification, 8-fold cross-validation was performed on the bone suppression model. In terms of evaluating the COVID-19 classification, the CXR images obtained by the improved method were used to train 2 classification models.

Results

Compared with other methods, the CXR images obtained based on the proposed model had better performance in the metrics of peak signal-to-noise ratio and root mean square error. The super-resolution CXR images of bone suppression obtained based on the neural network model were also anatomically close to the real CXR images. Compared with the initial CXR images, the classification accuracy rates of the internal and external testing data on the VGG-16 model increased by 5.09% and 12.81%, respectively, while the values increased by 3.51% and 18.20%, respectively, for the ResNet-18 model. The numerical results were better than those of the single-enhancement, double-enhancement, and no-enhancement CXR images.

Conclusions

The multistrategy enhanced CXR images can help to classify COVID-19 more accurately than the other existing methods.

Immune related biomarkers for cancer metastasis to the brain

Brain metastasis accounts for a large number of cancer-related deaths. The host immune system, involved at each step of the metastatic cascade, plays an important role in both the initiation of the brain metastasis and their treatment responses to various modalities, through either local and or systemic effect. However, few reliable immune biomarkers have been identified in predicting the development and the treatment outcome in patients with cancer brain metastasis. Here, we provide a focused perspective of immune related biomarkers for cancer metastasis to the brain and a thorough discussion of the potential utilization of specific biomarkers such as tumor mutation burden (TMB), genetic markers, circulating and tumor-infiltrating immune cells, cytokines, in predicting the brain disease progression and regression after therapeutic intervention. We hope to inspire the field to extend the research and establish practical guidelines for developing and validating immune related biomarkers to provide personalized treatment and improve treatment outcomes in patients with metastatic brain cancers.

A Transfer Learning Framework for Deep Learning-Based CT-to-Perfusion Mapping on Lung Cancer Patients

Purpose

Deep learning model has shown the feasibility of providing spatial lung perfusion information based on CT images. However, the performance of this method on lung cancer patients is yet to be investigated. This study aims to develop a transfer learning framework to evaluate the deep learning based CT-to-perfusion mapping method specifically on lung cancer patients.

Methods

SPECT/CT perfusion scans of 33 lung cancer patients and 137 non-cancer patients were retrospectively collected from two hospitals. To adapt the deep learning model on lung cancer patients, a transfer learning framework was developed to utilize the features learned from the non-cancer patients. These images were processed to extract features from three-dimensional CT images and synthesize the corresponding CT-based perfusion images. A pre-trained model was first developed using a dataset of patients with lung diseases other than lung cancer, and subsequently fine-tuned specifically on lung cancer patients under three-fold cross-validation. A multi-level evaluation was performed between the CT-based perfusion images and ground-truth SPECT perfusion images in aspects of voxel-wise correlation using Spearman’s correlation coefficient (R), function-wise similarity using Dice Similarity Coefficient (DSC), and lobe-wise agreement using mean perfusion value for each lobe of the lungs.

Results

The fine-tuned model yielded a high voxel-wise correlation (0.8142 ± 0.0669) and outperformed the pre-trained model by approximately 8%. Evaluation of function-wise similarity indicated an average DSC value of 0.8112 ± 0.0484 (range: 0.6460-0.8984) for high-functional lungs and 0.8137 ± 0.0414 (range: 0.6743-0.8902) for low-functional lungs. Among the 33 lung cancer patients, high DSC values of greater than 0.7 were achieved for high functional volumes in 32 patients and low functional volumes in all patients. The correlations of the mean perfusion value on the left upper lobe, left lower lobe, right upper lobe, right middle lobe, and right lower lobe were 0.7314, 0.7134, 0.5108, 0.4765, and 0.7618, respectively.

Conclusion

For lung cancer patients, the CT-based perfusion images synthesized by the transfer learning framework indicated a strong voxel-wise correlation and function-wise similarity with the SPECT perfusion images. This suggests the great potential of the deep learning method in providing regional-based functional information for functional lung avoidance radiation therapy.

Potential Determinants for Radiation-Induced Lymphopenia in Patients With Breast Cancer Using Interpretable Machine Learning Approach

Radiation-induced lymphopenia is known for its survival significance in patients with breast cancer treated with radiation therapy. This study aimed to evaluate the impact of radiotherapy on lymphocytes by applying machine learning strategies. We used Extreme Gradient Boosting (XGboost) to predict the event of lymphopenia (grade≥1) and conduced an independent validation. Then, we induced feature attribution analysis (Shapley additive explanation, SHAP) in explaining the XGboost models to explore the directional contribution of each feature to lymphopenia. Finally, we implemented the proof-of-concept clinical validation. The results showed that the XGboost models had rigorous generalization performances (accuracies 0.764 and ROC-AUC 0.841, respectively) in the independent cohort. The baseline lymphocyte counts are the most protective feature (SHAP = 5.226, direction of SHAP = -0.964). Baseline platelets and monocytes also played important protective roles. The usage of taxane only chemotherapy was less risk on lymphopenia than the combination of anthracycline and taxane. By the contribution analysis of dose, we identified that firstly lymphocytes were sensitive to a radiation dose less than 4Gy; secondly the irradiation volume was more important in promoting lymphopenia than the irradiation dose; thirdly the irradiation dose promoted the event of lymphopenia when the irradiation volume was fixed. Overall, our findings paved the way to clarifying the radiation dose volume effect. To avoid radiation-induced lymphopenia, irradiation volume should be kept to a minimum during the planning process, as long as the target coverage is not compromised.

Early onset of severe lymphopenia during definitive radiotherapy correlates with mean body dose and predicts poor survival in cervical cancer

BACKGROUND:

Lymphopenia during definitive radiotherapy (RT) has been shown to reduce survival in patients with cervical cancer. However, there are few studies on the significance of onset time of lymphopenia during RT in patients with cervical cancer.

OBJECTIVE:

This study aimed to exam the prognostic significance of early onset of severe lymphopenia (EOSL) during definitive RT in patients with cervical cancer.

METHODS:

Newly diagnosed cervical cancer patients treated with definitive RT from January 2015 to December 2019 were eligible for this retrospective study. EOSL was defined as first onset of grade 3–4 lymphopenia ⩽ 3 weeks from the start of RT. Mean body dose (MBD) was the mean radiation dose absorbed by the body during the whole course of external beam RT (EBRT) and was directly obtained from the dose volume histogram (DVH) of the EBRT planning. Logistic regression analysis and restricted cubic spline (RCS) models were applied to assess relationships between clinicopathological factors and EOSL. Survival analysis was performed using Kaplan-Meier curves and log-rank test. A COX regression model was developed to predict overall survival (OS).

RESULTS:

A total of 104 patients were included and 59.6% had EOSL. MBD (P= 0.04), concurrent cisplatin (P= 0.011), and pre-RT absolute lymphocyte count (ALC) (P= 0.001) were associated with EOSL. A linear relationship (P for non-linearity = 0.803) between MBD and risk of EOSL was found. Patients with EOSL had decreased OS (2-yr 75.1% vs 91.1%, P= 0.021) and progression-free survival (PFS) (2-yr 71.2% vs 83.7%, P= 0.071). An OS prediction COX model was developed with C-index of 0.835 and AUC of 0.872.

CONCLUSIONS:

EOSL during definitive RT correlates with MBD and predicts poor survival in patients with cervical cancer.

Genetic Variations in the Transforming Growth Factor-β1 Pathway May Improve Predictive Power for Overall Survival in Non-small Cell Lung Cancer

Purpose: Transforming growth factor-β1 (TGF-β1), a known immune suppressor, plays an important role in tumor progression and overall survival (OS) in many types of cancers. We hypothesized that genetic variations of single nucleotide polymorphisms (SNPs) in the TGF-β1 pathway can predict survival in patients with non-small cell lung cancer (NSCLC) after radiation therapy. Materials and Methods: Fourteen functional SNPs in the TGF-β1 pathway were measured in 166 patients with NSCLC enrolled in a multi-center clinical trial. Clinical factors, including age, gender, ethnicity, smoking status, stage group, histology, Karnofsky Performance Status, equivalent dose at 2 Gy fractions (EQD2), and the use of chemotherapy, were first tested under the univariate Cox's proportional hazards model. All significant clinical predictors were combined as a group of predictors named "Clinical." The significant SNPs under the Cox proportional hazards model were combined as a group of predictors named "SNP." The predictive powers of models using Clinical and Clinical + SNP were compared with the cross-validation concordance index (C-index) of random forest models. Results: Age, gender, stage group, smoking, histology, and EQD2 were identified as significant clinical predictors: Clinical. Among 14 SNPs, BMP2:rs235756 (HR = 0.63; 95% CI:0.42-0.93; p = 0.022), SMAD9:rs7333607 (HR = 2.79; 95% CI 1.22-6.41; p = 0.015), SMAD3:rs12102171 (HR = 0.68; 95% CI: 0.46-1.00; p = 0.050), and SMAD4: rs12456284 (HR = 0.63; 95% CI: 0.43-0.92; p = 0.016) were identified as powerful predictors of SNP. After adding SNP, the C-index of the model increased from 84.1 to 87.6% at 24 months and from 79.4 to 84.4% at 36 months. Conclusion: Genetic variations in the TGF-β1 pathway have the potential to improve the prediction accuracy for OS in patients with NSCLC.

Association of Twice-Daily Radiotherapy With Subsequent Brain Metastases in Adults With Small Cell Lung Cancer

IMPORTANCE

Although thoracic twice-daily radiotherapy (TDRT) is one of the standards of care for small cell lung cancer, its association with brain metastases remains unknown.

OBJECTIVE

To investigate the association of TDRT vs once-daily radiotherapy (ODRT) with brain metastases after prophylactic cranial irradiation in patients with small cell lung cancer.

DESIGN, SETTING, AND PARTICIPANTS

In this multicenter cohort study, data on 778 consecutive patients with small cell lung cancer who had undergone thoracic radiotherapy (609 received ODRT and 169 received TDRT), chemotherapy, and prophylactic cranial irradiation were retrieved from the databases of 8 hospitals in China between July 1, 2003, and June 30, 2016. A 1:1 propensity score matching approach was used to control for confounding between the ODRT and TDRT groups. Confounding covariates included 8 demographic variables and 8 treatment-related covariates. Data analysis was conducted from November 1, 2017, to May 31, 2018, and reanalyzed for revision.

EXPOSURES

The ODRT group received 50 to 66 Gy given in 25 to 33 fractions. The TDRT group received 45 Gy given in 30 fractions.

MAIN OUTCOMES AND MEASURES

The primary end point was brain metastases. Secondary end points included progression-free survival and overall survival.

RESULTS

Of the 778 patients (median age, 55 years [interquartile range, 48-61 years]), 204 were women and 574 were men. At a median follow-up of 23.6 months (interquartile range, 14.2-38.2 months), 131 patients (16.8%) experienced brain metastases. The rate of brain metastasis at 3 years in the TDRT group was significantly higher than in the ODRT group (26.0% vs 16.9%; hazard ratio, 1.55; 95% CI, 1.06-2.26; P = .03). Of the 338 matched patients (169 in the ODRT group vs 169 in the TDRT group), 60 (17.8%) experienced brain metastases, with a rate at 3 years of 14.9% in the ODRT group vs 26.0% in the TDRT group (hazard ratio, 1.71; 95% CI, 1.02-2.88; P = .04). Progression-free survival was similar in both the whole cohort and the matched cohort. Median overall survival in the ODRT group tended to be significantly longer than in the TDRT group after matching (47.2 vs 32.8 months; hazard ratio, 1.41; 95% CI, 0.99-2.01; P = .06).

CONCLUSIONS AND RELEVANCE

In this study, patients with small cell lung cancer who received thoracic TDRT appeared to have a higher risk of brain metastases than those who received ODRT, which supports the need for further prospective randomized clinical trials, especially in China and other parts of Asia.

Kinetics and dosimetric predictors of acute radiation-induced lymphopenia in pancreatic cancer

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Background: Radiation (RT) induced lymphopenia (RIL) is an adverse prognostic factor in pancreatic cancer (PC) and is likely due to the irradiation of lymphocytes in the RT field. The goal of this study was to identify dosimetric predictors for high rates of absolute lymphocyte count (ALC) loss during RT for PC. Methods: This was a retrospective study of 34 PC patients in an institutional database who had received concurrent 5-FU or gemcitabine-based chemoradiation (50-54 Gy) and had ≥ 3 ALCs measured during RT. Baseline ALC was normal (>1000 cells/uL) in 28/34 (82%) and grade 3-4 RIL occurred in 24/34 (71%). ALC was plotted against fraction # and a best-fit line for each patient was created to determine per-fraction loss in ALC (PFLAC). Linear regression was used to correlate PFLAC with dosimetric parameters including mean dose to gut, liver, kidney, spleen, and cisterna chyli, as well as estimated dose to immune cells (EDIC), which calculates dose to immune cells according to the % of body lymphocytes contained in each organ. Results: All patients exhibited exponential loss in ALC during RT. Mean PFLAC was 6.8% (range 1.7-13.4); fraction # was strongly correlated with ALC (mean R2 = 0.89). Patients with >/= grade 3 lymphopenia had a significantly higher PFLAC than those with grade 0 - 2 lymphopenia (mean daily loss 7.8% in Gr 3-4 vs. 4.8% in Gr 0-2, p = 0.001; independent sample T test). Field size was not correlated with PFLAC for high (> 1 Gy) or low (< 0.5 Gy) isodose volumes. Mean whole body (r = 0.59, p < 0.001), bowel (r = 0.39, p = 0.012), liver (r = 0.42, p = 0.007), and cisterna chyli (r = 0.583, p = 0.004) doses were moderately correlated with PFLAC; mean kidney (r = 0.22, p = 0.11) and spleen (r = 0.26, p = 0.06) doses were weakly correlated with PFLAC. EDIC was more strongly correlated with PFLAC than any individual organ mean dose (r = 0.69, p < 0.001). Conclusions: Patients undergoing RT for PC experience a predictable RIL characterized by an exponential loss of lymphocytes per day. PFLAC is a useful method of characterizing RIL and facilitates evaluation of dosimetric predictors of RIL. We identified dose to cisterna chyli as a significant contributor to RIL in PC; however, EDIC has a stronger correlation with RIL severity than any single organ dose.

Survival in patients with hepatocellular carcinoma (HCC): A report of 1444 patients treated within a multidisciplinary program

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Background: The evolution of treatment for HCC has seen novel therapies emerge as front line treatment alternatives. The aim of this study was to report survival in HCC patients treated within the context of a robust multidisciplinary program and to identify patient and tumor specific factors that direct patient centered treatment decisions and optimize outcome. Methods: This is retrospective analysis of medical records identified through the cancer registry at our institution from 2000 to 2016. Variables analyzed for survival significance included patient factors (age, gender, race, tobacco history, alcohol history, and marital status) and tumor factors (tumor size, histology grade, AFP level, SEER stage, clinical and pathologic stage). Survival was estimated from the time of diagnosis to the last contact. Results: A total of 1444 consecutive patients with confirmed HCC were eligible for this analysis. Median follow-up was 45 months. Median survival was 18 months (95% CI: 11-25 months). The overall 1-, 3-, and 5-year survival rates were 63, 40, and 35%, respectively. Significant prognostic parameters were SEER stage (HR = 2.3, p = 2x10-16 local as the reference), pathologic stage (HR = 1.2, p = 3×10-9), tobacco history (HR = 1.2, p = 0.03), , and clinical stage (HR = 1.1, p = 4x10-5). Of a total of 380 patients resected, median and 3-year survival were 75 months and 63% (95% CI: 58-69%). The only significant prognostic parameter associated with survival in resection patients was SEER stage (HR = 1.7, p = 0.002). The 5 year survival for all patients versus those resected were 44% (95% CI: 40-48) /59% (95% CI: 53-65), 21% (95% CI: 17-27) /36% (95% CI: 24-54), and 11% (95% CI: 5-20) /25% (95% CI: 6-100) for localized, regional, and distant disease, respectively. Conclusions: Survival has improved for patients with HCC due to an increased number of available options and better methods to identify tumor and patients specific variables that individualize care. The significance of SEER stage suggests that early detection remains critical for survival.

Paraneoplastic syndrome and survival in thymic epithelial tumors (TET): The Indiana University experience

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Background: Paraneoplastic syndromes (PNS) are commonly associated with thymic epithelial tumors (TET), especially thymoma. The purpose of this analysis is to examine the clinical impact of PNS in TET. Methods: Patients with pathologically diagnosed TET at a single institution were reviewed retrospectively. The primary and second endpoints for this study were overall survival (OS) and recurrence rates. Clinical factors included age, gender, race, performance score, histology, WHO classification, Masaoka stage, post-operative status, tumor size and number of positive lymph nodes. Cox proportional hazards model was used to identify significant prognostic factors for OS between different PNS groups. Results: From 1975 to 2016, 733 patients with TET (thymoma (T) -71%, thymic carcinoma (TC) -26% and neuroendocrine tumor (NET)-3%) were seen at Indiana University. Of these, 203 (28%) had PNS including myasthenia gravis (n = 130), red cell aplasia (n = 20), hypogammaglobulinemia (n = 14), systemic lupus erythematosus (n = 12) or other PNS (n = 64). Among these, 37 (18%) had two or more types of PNS. PNS were seen in 35% (183/523) of T, 9% (16/187) of TC and 15% (3/20) of NET ( p < 0.001), respectively. Recurrence rates and mortality at 5 year were 8% and 10% in PNS (+) group compared to 13% and 16% in PNS (-) group ( p < 0.05). Intrathoracic recurrences were more common in PNS (+) patients (89% vs 77%; p = 0.016). In both groups, adverse factors for survival included: older age, advanced stage, number of positive lymph nodes and TC histology (all p-values < 0.05). However, post-operative R1/2 status was adverse prognostic factor only in the PNS (-) group ( p = 0.001). Conclusions: PNS is common in TETs. Patients with PNS have lower risk of recurrence and mortality compared to patients without PNS, but may have a higher risk of intrathoracic recurrence.

Treatment-Related Death during Concurrent Chemoradiotherapy for Locally Advanced Non-Small Cell Lung Cancer: A Meta-Analysis of Randomized Studies

Treatment related death (TRD) is the worst adverse event in chemotherapy and radiotherapy for patients with cancer, the reports for TRDs were sporadically. We aimed to study TRDs in non-small cell lung cancer (NSCLC) patients treated with concurrent chemoradiotherapy (CCRT), and determine whether high radiation dose and newer chemotherapy regimens were associated with the risk of TRD. Data from randomized clinical trials for locally advanced/unresectable NSCLC patients were analyzed. Eligible studies had to have at least one arm with CCRT. The primary endpoint was TRD. Pooled odds ratios (ORs) for TRDs were calculated. In this study, a total of fifty-three trials (8940 patients) were eligible. The pooled TRD rate (accounting for heterogeneity) was 1.44% for all patients. In 20 trials in which comparison of TRDs between CCRT and non-CCRT was possible, the OR (95% CI) of TRDs was 1.08 (0.70-1.66) (P = 0.71). Patients treated with third-generation chemotherapy and concurrent radiotherapy had an increase of TRDs compared to those with other regimens in CCRT (2.70% vs. 1.37%, OR = 1.50, 95% CI: 1.09-2.07, P = 0.008). No significant difference was found in TRDs between high (≥ 66 Gy) and low (< 66 Gy) radiation dose during CCRT (P = 0.605). Neither consolidation (P = 0.476) nor induction chemotherapy (P = 0.175) had significant effects with increased TRDs in this study. We concluded that CCRT is not significantly associated with the risk of TRD compared to non-CCRT. The third-generation chemotherapy regimens may be a risk factor with higher TRDs in CCRT, while high dose radiation is not significantly associated with more TRDs. This observation deserves further study.

Metabolic response assessment with 18F-FDG PET/CT: inter-method comparison and prognostic significance for patients with non-small cell lung cancer

OBJECTIVE

This study aimed to (1) compare the agreement of two evaluation methods of metabolic response in patients with non-small cell lung cancer (NSCLC) and determine their prognostic value and (2) explore an optimal cutoff of metabolic reduction to distinguish a more favorable subset of responders.

METHODS

This is a secondary analysis of prospective studies. Enrolled patients underwent 18F-PET/CT within 2 weeks before, during, and months after radiotherapy (post-RT). Metabolic response was assessed using both Peter MacCallum (PM) method of qualitative visual assessment and University of Michigan (UM) method of semiquantitative measurement. The agreement between two methods determined response, and their prediction of outcome was analyzed.

RESULTS

Forty-four patients with median follow-up of 25.2 months were analyzed. A moderate agreement was observed between PM- and UM-based response assessment (Kappa coefficient = 0.434), unveiling a significant difference in CMR rate (p = 0.001). Categorical responses derived from either method were significantly predictive of overall survival (OS) and progression-free survival (PFS) (p < 0.0001). Numerical percentage decrease of FDG uptake also showed significant correlations with survival, presenting a hazard ratio of 0.97 for both OS and PFS. A 75 % of SUV decrease was found to be the optimal cutoff to predict OS and 2-year progression.

CONCLUSIONS

There was a modest discrepancy in metabolic response rates between PM and UM criteria, though both could offer predictive classification for survival. The percentage decrease provides an ordinal value that correlates with prolonged survival, recommending 75 % as the optimal threshold at identifying better responders.

Radiation dose effect in locally advanced non-small cell lung cancer

Radiation is the foundation of treatment for locally advanced non-small cell lung cancer (NSCLC), and as such, optimal radiation dose is essential for successful treatment. This article will briefly review biological considerations of radiation dose and their effect in the context of three-dimensional conformal radiation therapy (3D-CRT) including intensity modulated radiation therapy (IMRT) and stereotactic body radiation therapy (SBRT) for NSCLC. It will focus on literature review and discussions regarding radiation dose effect in locally advanced NSCLC including potential severe and lethal toxicities of high dose radiation given with concurrent chemotherapy. Potential new approaches for delivering safe and effective doses by individualizing treatment based on functional imaging are being applied in studies such as the PET boost trial and RTOG1106. The RTOG concept of delivering high dose radiation to the more resistant tumors with the use of isotoxic dose prescription and adaptive planning will also be discussed in detail.

Serum miRNA signature to identify a patient’s resistance to high-dose radiation therapy for unresectable non-small cell lung cancer

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Background: There is a growing literature on unique profiles of serum micro RNAs (miRNAs) expression to predict clinical outcome of metastatic and early stage non-small cell lung cancer (NSCLC). However, the predictive role of circulating miRNAs in unresectable NSCLC treated with definitive radiation therapy (RT) is unknown. Methods: 134 patients with inoperable/unresectable NSCLC treated with definitive RT (18-month minimum follow-up) were eligible. Serum samples were collected prospectively before treatment. 100 patients had enough serum and reliable miRNA profile quality, which were randomly divided into training and validation sets (50 patients each). MiRNA profiling was performed using real-time PCR-based array, containing a panel of 84 miRNAs detectable in human bodily fluids. Spiked-in cel-miR-39 was used for normalization. Stepwise regression Cox model building was used to build a miRNA signature on the training set, which was then assessed on the validation set both alone and with clinical factors. Results: The median age was 67 years; 76% were stages III and 79% received chemoradiation; the median physical dose was 70.0 Gy. A serum hsa-miR-885/hsa-miR-7 signature was identified as significant predictors for overall survival (OS) in the training set, which was validated by the validation set (p=0.02). After adjustment for GTV Volume and KPS, the only two significant clinical factors in univariate analysis, this signature remained significant (p=0.04). In the high-dose RT group (>70 Gy, n=45), individuals with low-risk had a significantly longer OS than patients with high-risk (70.7 vs. 18.8 months, p=0.007); while in the low-dose RT group (≤70 Gy, n=55), no significant association was observed (OS, 22.0 vs. 13.3 months, p=0.43). Conclusions: Circulating hsa-miR-885/hsa-miR-7 signature may be used as a putative non-invasive biomarker for predicting survival and radiation resistance in unresectable NSCLC, which may potentially help to select patients who will not benefit from high-dose radiation. Independent validation studies are needed to confirm our findings. Clinical trial information: NCT01190527.

Total lesion glycolysis (TLG) at baseline FDG-PET/CT compared with maximum standard uptake value (SUVmax) to predict survival in non-small cell lung cancer (NSCLC)

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Background: SUVmaxat baseline FDG-PET has been reported as a significant prognostic factor while recent studies suggest that metabolic tumor volume (MTV) may be more important factor in patients with NSCLC. We hypothesized that TLG is a better prognostic factor than either SUVmax or MTV alone for overall survival (OS) and progression free survival (PFS) in NSCLC because it integrates both volumetric and biologic activity. Methods: The study population included a prospectively recruited cohort of stage I-III NSCLC patients treated with chemoradiation. FDG PET/CT scans were performed within 2 weeks from treatment start. The SUV in the tumor was normalized to that of the background level in the middle of ascending aorta to minimize the confounding effect from inter-scan variation in SUV measurement. MTV was delineated by auto-threshold at 1.5 times background level in the aorta followed by knowledge based manual editing. Mean and maximum SUV normalized to the background level were computed. TLG was calculated as the product of lesion SUVmean and MTV. Results: A total of 96 patients with minimum follow-up of 1 year were eligible. The median follow-up among survivors was 30 months. Univariate analysis demonstrated that MTV and TLG were significant factors for both OS and PFS (all P<0.05). There was a significant correlation between SUVmean and PFS (P=0.013), but there was no significant association between SUVmean and OS. SUVmax was not a significant factor for either OS or PFS (all P>0.05). Under multivariate Cox regression analysis, MTV (HR= 2.62, P= 0.003) and NSUVmean (HR=0.351, P=0.003) were significantly associated with PFS; but only TLG was significantly associated with OS (HR=2.14, P=0.006)adjusted by of TNM stage and other clinical factors. Conclusions: These results support our hypothesis that metabolic tumor volume and biologic average glucose metabolic activity of this volume are more important prognostic factors for overall prognosis than SUVmax in NSCLC patients treated with chemoradiation. Should this be validated by independent studies, future clinical trial should take this into consideration for individualized care.

The association of plasma TGFβ1 during radiotherapy and genotypes of TGFβ1 pathway in patients with non-small cell lung cancer

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Background: Radiation induced thoracic toxicities (RITT) in lung, esophagus and pericardium are dose-limited toxicities in patients with non-small cell lung cancer (NSCLC). Plasma transforming growth factor-beta1 (TGFβ1) and its change during radiotherapy was reported as a biomarker and single nucleotide polymorphisms (SNP) in TGFβ1 pathway was associated with RITT in our previous studies. In order to explore the mechanism of RITT, we tested whether plasma TGFβ1 was associated with genotypes of TGFβ1, tissue plasminogen activator (tPA) and angiotensin converting enzyme (ACE). Methods: Patients with stage I-III NSCLC enrolled in prospective clinical trials were eligible. All patients received radiotherapy with or without concurrent chemotherapy. Platelet-poor plasma was obtained pre-RT and at 4–5 weeks (40–50 Gy) during RT. Plasma TGF-β1 was measured using an enzyme-linked immunosorbent assay. The DNA samples extracted from blood before treatment were analyzed for the following genetic variations: TGFβ1 509C/T, TPA -7351 C/T, and ACE I/D. Results: 76 NSCLC patients received definitive radiotherapy (median dose 66 Gy) were enrolled. For the entire group of patients, the mean pre-RT TGFß1 level was 10.7±2.3 ng/ml, and the mean during-RT TGFß1 level was 6.0±0.7 ng/ml. No significant TGFß1 level differences were found at pre-RT and during-RT in patients with different genotypes of TGFß1 and tPA. Only ACE DD group had marginally higher pre-RT TGFß1 level than II and ID group (DD 23.6ng/ml vs. II 9.0ng/ml vs. ID 7.5ng/ml, p = 0.05), but no difference at during-RT(p=0.346) or during-RT/pre-RT ratio(p = 0.433). However, patients with TGFß1 509CC had higher elevation of plasma TGF ß1 level at fourth week during-RT than T allele carriers (TGFß1 level ratio of during-RT/pre-RT were CC 1.4±0.2 vs. T allele carriers 0.7±0.1, p=0.047). Conclusions: This exploratory study demonstrated that patients with TGFß1 509CC had higher elevation of plasma TGF ß1 level at fourth week during-RT than T allele carriers. This can help explain the correlation of TGF ß1 level elevation and higher risk of radiation induced lung toxicity in patients with NSCLC.

Association between genetic variations in transforming growth factor beta pathway and overall survival in patients with non-small cell lung cancer treated with definitive radiotherapy

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Background: The transforming growth factor beta (TGFβ) pathway, an important regulator in cellular metabolic process, has been reported for significant association with cancer prognosis. This study was to exam the association between single nucleotide polymorphisms (SNPs) of TGFβ pathway and overall survival (OS) in subjects with non-small cell lung cancer (NSCLC). Methods: Patients with stage I-III NSCLC received definitive radiotherapy with/without chemotherapy were eligible to this prospective study. The primary endpoint was OS which was calculated from radiation treatment start to death or censored. DNA samples for genotyping were extracted from buffy-coat which was collected before commencement of treatment. 19 SNPs in 10 genes (BMP1, BMP2, INHBC, SMAD1, SMAD3, SMAD4, SMAD6, SMAD7, SMAD8, TGFβ1), which was reported to have significant correlation with OS of lung cancer, were selected. MassArray System (Sequenom Company) was used for genotyping. Cox regression was performed for multivariate analysis to examine the effects of genotypes on OS using dominant and recessive genetic model. Results: 126 consecutive patients, 91% of them were Caucasian, were recruited in this study. All SNPs call rates were over 90%. Assay reproducibility was over 99% by random double-blinding duplicate or triplicate genotyping. Among clinical factors analyzed, radiation dose was only significant independent factor predicting OS (P=0.001). Genotypic association study showed that 7 SNPs (rs235756, rs11939979, rs12102171, rs6494633, rs12456284, rs12906898 and rs4803455) were significantly associated with OS, adjusted for age, gender, smoking, histology, clinical stage, tumor volume, Karnofsky Performance Status, radiotherapy dose, and chemotherapy. The strongest association was in SMAD3: rs12102171 (P=0.004, HR=2.28, 95%CI, 1.26-4.15). Conclusions: This study partly validated findings from previous studies that genetic variations in the TGFβ pathway are significant predictors of overall survival in NSCLC patients treated with definitive radiotherapy with/without chemotherapy.