bluuebunny/crossref_metadata_2025_split huggingface dataset:
The frequency of chromosomal abnormalities in AL amyloidosis and their impact on treatment response.
Authors: Yameen Hassan , Sarosiek Shayna , Sanchorawala Vaishali 
Published: March 2020

e19539 Background: Chromosomal abnormalities (CA) found in AL amyloidosis (AL) are similar to those found in multiple myeloma (MM.) However, t(11;14) has been reported more frequently in AL, anywhere from 30% - 50% in studies. It has been reported that the presence of t(11;14) confers a lower hematologic response rate with bortezomib-based therapy (BBT) and a better hematologic response rate with high dose melphalan and autologous stem cell transplantation (HDM/SCT). Methods: We performed a retrospective review of 307 newly diagnosed patients seen at our center between January 2013 and December 2017, for whom interphase fluorescent in-situ hybridization (iFISH) data, performed on bone marrow aspirate using standard MM FISH probes on enriched plasma cells after magnetic separation, were available. Patients who already had iFISH performed prior to their visit with us were also included. We collected data on the incidence of CA, first line treatment, and hematologic response to this treatment. Results: Of the 307 patients, CA were not detected in 37%. 21% had t(11;14), 25% had 13q deletion, 21% had IgH rearrangements with an undetermined partner chromosome, and 11% had 1q21 gain. In those for whom initial treatment and hematologic response data were available, in patients with t(11;14), hematologic complete response (CR) was achieved by 18% following HDM/SCT and 27% following BBT. For those with 1q21 gain, CR was achieved by 33% following HDM/SCT and 19% following BBT. In contrast, hematologic CR was achieved by 47% following HDM/SCT and 40% following BBT for those who had no detectable CA with iFISH. Conclusions: Our study shows a lower incidence of t(11;14) in AL compared to other studies. This may be partly explained by the high number of patients with IgH rearrangements with undetermined partner chromosomes, some of whom may indeed harbor t(11;14). Our study also did not show a better hematologic response rate with HDM/SCT in t(11;14) patients compared with BBT. Hematologic response rates were much better both with HDM/SCT and BBT for those with no detected CA compared to patients who had t(11;14) or 1q21 gain.
Association between smoking status and lymph node metastasis in Chinese patients with T1 non-small cell lung cancer: A real-world observational study.
Authors: Jiang Feng , Zhao Heng , Li Xiaofei , Liu Lunxu , Liu Yang , Hu Jian , Fu Xiangning , Li Yin , Xu Yijun , Liu Deruo , Yang Haiying , Xu Lin 
Published: March 2020

e20012 Background: Smoking and lymph node metastasis (LNM) are widely known to be the important risk factor for the induction and poor prognosis of non-small cell lung cancer (NSCLC) , respectively. However, the association between smoking status and LNM in Chinese patients with NSCLC is largely unknown. Methods: The patients with pathologically diagnosed T1 NSCLC undergoing surgical resection during 2014 to 2017 were retrospectively reviewed based on LinkDoc database. Patients without smoking status in the case records were excluded. Chi-square test was used for comparison between groups. Results: Of the 10,622 patients enrolled, 1,760 patients had LNM (16.6%). For smoking status, 3,260 (30.7%) patients were recorded with smoking history, with an average smoking index (SI) of 221.2. The incidence of LNM especially N2 station LNM in patients who ever smoked was significantly higher than those of never smokers in the enrolled population (22.8% vs. 13.6%, p < 0.001; N2: 14.3% vs. 9.1%, p < 0.001). Similarly, a larger proportion of current smokers than never smokers had LNM (24.0% vs. 13.6%, p < 0.001), and also more current smokers in only N2 station LNM (14.1% vs. 9.1%, p < 0.001). However, no statistically difference was observed in the proportion of patients with LNM particularly with N2 LNM between former and current smokers (24.0% vs. 22.8%, p = 0.401; N2: 14.1% vs. 14.3%, p = 0.887). Compared with non to light smoking (SI < = 400), patients with middle to heavy smoking ( > 400) were found to be more likely to develop LNM (N1/N2: 24.8% vs. 14.6%, p < 0.001; N2: 14.3% vs. 9.8%, p < 0.001). Conclusions: These findings from the real-world study indicated a close association between smoking both former and current and LNM especially N2 station LNM in patients with T1 NSCLC. [Table: see text]
A nomogram to predict outcomes of lung cancer patients after pneumonectomy based on 47 indicators.
Authors: Cheng Bo , Wang Cong , Meng Xue 
Published: March 2020

e20014 Background: Nomograms are commonly used tools to estimate prognosis in oncology and medicine.We aimed to establish a nomogram with patients’ characteristics and all available hematological biomarkers for lung cancer patients. Methods: All indexes were cataloged according to clinical significance. Principle component analysis (PCA) was used to reduce the dimensions. Each component was transformed into categorical variables based on recognized cut-off values from receiver operating characteristic (ROC) curve. Kaplan-Meier analysis with log-rank test was used to evaluate the prognostic value of each component. Multivariate analysis was used to determine the promising prognostic biomarkers. Five components were entered into a predictive nomogram. The model was subjected to bootstrap internal validation and to external validation with a separate cohort from Shandong Cancer Hospital. The predictive accuracy and discriminative ability were measured by concordance index (C index) and risk group stratification. Results: Two hundred thirty-six patients were retrospectively analyzed in this study, with 134 in the Discovery Group and 102 in the Validation Group. Forty-seven indexes were sorted into 8 subgroups, and 20 principle components were extracted for further survival analysis. Via cox regression analysis, five components were significant and entered into predictive nomograms. The calibration curves for probability of 3-, and 5-year overall survival (OS) showed optimal agreement between nomogram prediction and actual observation. The new scoring system according to nomogram allowed significant distinction between survival curves within respective tumor-node-metastasis (TNM) subgroups. Conclusions: A nomogram based on the clinical indexes was established for survival prediction of lung cancer patients, which can be used for treatment therapy selection and clinical care option. PCA makes big data analysis feasible.
Can smoking duration alone replace pack-years to predict the risk of smoking-related oncogenic mutations in non-small cell lung cancer (NSCLC)?
Authors: Ogawa Koichi , Kawaguchi Tomoya , Koh Yasuhiro , Isa Shun-Ichi , Kubo Akihito , Ando Masahiko , Saka Hideo , Yoshimoto Naoki , Matsumura Akihide , Kaneda Hiroyasu , Tamiya Akihiro , Taniguchi Yoshihiko , Sawa Kenji , Matsumoto Yoshiya , Izumi Motohiro 
Published: March 2020

e20017 Background: P has widely been used for the risk assessment of lung cancer and chronic obstructive pulmonary disease (COPD). We previously reported that mutations in KRAS, TP53, and EGFR were also associated with P from a prospective multicenter molecular epidemiology study (JME study; Kawaguchi T, J Clin Oncol 2016). Recently, D alone has been reported to provide stronger risk estimates of COPD than P. Here, we show the comparison of these two indices in predicting the risk of smoking-related oncogenic mutations in NSCLC, utilizing the database from the JME study including detailed smoking information and the mutational profile by next generation sequencing. Methods: In 439 ever- and 437 never-smokers, the frequency of mutations in KRAS, TP53 and EGFR were 9.4, 26.8 and 42.5%, respectively, and smoking-related cytosine to adenine base substitution (C > A) was observed in 12.7 % of cases. AUC values (area under the ROC curves) for logistic regression determined from P and D to predict the mutations or C > A change were compared, considering gender, age, stage and histology as covariates. Results: The median of P and D were 43 (1-189) and 41 (years, 1-65) in smokers, respectively. The AUC values in EGFR and KRAS were numerically higher than others, suggesting stronger association with smoking. There was no significant difference in AUC values between P and D in TP53, EGFR and C > A, and P was a significantly better estimate of KRAS mutations (table). Conclusions: P remains the standard method to evaluate the risk of oncogenic mutations in NSCLC. D, however, warrants further investigation as a simpler alternative to P.[Table: see text]
Correlation of tumor mutational burden, tumor microenvironment and alterations of driver genes in patients with NSCLC: A retrospective analysis.
Authors: Yu Yao , Lin Rongbo , He Ning , Yang Yadong , Jin Ge , Wang Jianfei 
Published: March 2020

e20019 Background: To investigate the correlation of tumor mutational burden, tumor microenvironment and alterations of driver genes in tumor tissue of patients with NSCLC. Methods: 79 patients with confirmed NSCLC admitted from January 2018 to January 2019 were included. Tumor DNA was isolated from FFPE samples or fresh tissue samples. Mutation profiles were obtained by targeted deep sequencing of 620 selected genes. Tumor mutational burden (TMB) was defined as the number of non-synonymous mutations per 1Mbp and divided into tertiles. PD-L1 expression, CD8+ T cell and tumor infiltrating lymphocyte density were evaluated by immunohistochemical analysis. The correlation coefficient of TMB, tumor microenvironment and alterations of driver genes was calculated by chi-square test. Results: Median TMB of these patients is 6.915 Muts/Mbp (4.22-9.44 Muts/Mbp). Prevalence of PD-L1 expression is 28.0% (n = 7/25) at a tumor proportion score cutoff of at least 5% evaluated by Dako 28-8 PharmDx Assay kit and prevalence of CD8+ T cell density is 95.8% (n = 23/24). TP53 mutations are the most common alteration (n = 49/79, 62.0%), followed by EGFR alterations (n = 31/79, 39.2%), CDKN2A alterations (n = 11/79, 13.9%), KRAS mutations (n = 10/79, 12.7%), STK11 mutations (n = 5/79, 6.3%), ALK fusions (n = 4/79, 5.1%) and POLE mutations (n = 4/79, 5.1%). According to results of chi-square test, squamous cell carcinoma has higher TMB (p= 0.023) than adenocarcinoma. Metastatic NSCLC has higher PD-L1 expression (p= 0.049) than non-metastatic NSCLC. Furthermore, EGFR alterations are associated with lower TMB (p=0.020) and POLE mutations are associated with higher TMB (p= 0.015). There are no correlations among CD8+ T cell density, tumor infiltrating lymphocyte density and other variants. Conclusions: Our study highlights the correlation of tumor mutational burden, tumor microenvironment and alterations of driver genes in patients with NSCLC. This result may be the reference of anti-PD-1 therapy.
The prognostic value of KRAS mutation subtypes and PD-L1 expression in patients with lung adenocarcinoma.
Authors: Tao Luwei , Sun Jingxin , Mekhail Tarek , Meng Lingbin , Fang Cheng , Du Yuan , Socinski Mark A. , Allen Amanda , Rzeszutko Brenda L. , Chang Chung-Che 
Published: March 2020

e20022 Background: KRAS gene mutations are found in 20-30% of non-small cell lung cancer (NSCLC), especially in adenocarcinoma. Compared to EGFR and ALK mutations, KRAS mutation in NSCLC may be associated with poorer prognosis. However, prognostic value of different KRAS mutation subtypes in NSCLC remains unknown. The goal of this study is to evaluate the association of KRAS mutation subtypes, PD-L1 expression and clinical outcome in patients diagnosed with primary lung adenocarcinoma. Methods: A total of 256 patients diagnosed with KRAS mutated (determined by pyrosequencing) lung adenocarcinoma between 2011 and 2015 in AdventHealth-Orlando were evaluated for their cancer staging, Relapse-free survival (RFS) and overall survival (OS). PD-L1 staining was performed in a subgroup of 95 patients from the same cohort. PD-L1 expression was determined with immunohistochemistry staining using Ventana PD-L1 (SP263) assay. Results: In this cohort of patients, 65 had stage I disease, 29 stage II, 49 stage III, 110 stage IV and 3 with no clinical stage information; 104 male, 152 female; median age 67. All patients received standard surgical/chemo/radio therapy according to the disease stages. Only one single patient received immunotherapy. Nine subtypes of KRAS mutation were detected, predominantly in codon 12. Three major subtypes account for 83.6% KRAS mutations, namely G12C (45.7%), G12V (21.9%) and G12D (16.0%). We found that these three major subtypes had no difference in cancer stages (P = 0.58) or brain metastasis at diagnosis (P = 0.78). Kaplan Meier analysis also showed similar OS and RFS among all KRAS subtype. 34% of KRAS mutated patients were found to be PD-L1 positive with tumor proportion score of greater than or equal to 1. PD-L1 expression status was indistinct among the three major mutation subtypes (P = 0.38). Of interest, among patients with G12C mutation, positive PD-L1 expression was associated with significantly shorter OS (5.7 vs 12.8 months; P = 0.007). In contrast, for patients with other KRAS mutation subtypes, PD-L1 expression status had no impact on OS (P = 0.63). Conclusions: The clinical courses, including tumor stage at diagnosis, presence of brain metastasis, OS and RFS, are similar among lung adenocarcinoma patients with different KRAS mutation subtypes. Additionally, PD-L1 expression status appears to be independent of KRAS mutation subtypes. Of note, concurrent PD-L1 expression and G12C mutation is associated with particularly poorer prognosis. Further study is needed to see if PD1/PD-L1 block may improve outcome of this group of patients.
Outcomes among patients with a history of substance abuse in non-small cell lung cancer: A county hospital experience.
Authors: Concannon Kyle , Thayer John Henry , Hicks Roxana , Wu Vicky , Jenkins Isaac , Baik Christina S , Linden Hannah M. 
Published: March 2020

e20031 Background: Insufficient outpatient care among vulnerable patients, such as those with a history of alcohol or illicit substance use disorder (SUD), may contribute to poor outcomes in non-small cell lung cancer (NSCLC). We hypothesize that patients with newly diagnosed localized NSCLC and a history of SUD have a shorter time from diagnosis to last known contact, greater rates of depression, less family support, poorer follow-up, and increased emergency room and inpatient usage compared to those without a history of SUD. Methods: To investigate this, we conducted a retrospective review of all lung cancer patients with localized non-small cell carcinoma (N = 52) with visits between 9/2012 and 9/2018 at an academic county hospital with a dedication to the underserved in a major US city. Data were collected from electronic medical records manually and analyzed using ANOVA for continuous variables or Pearson's Chi-squared for categorical data. Results: Among patients with localized NSCLC (n = 52), 44% had a history of SUD. The mean time from diagnosis to last known contact and rate of loss-to-follow-up among those with a history of SUD vs no history of SUD was: 2.9 vs 4.4 years (p = 0.14) and 26.1% vs 20.7% (p = 0.64) respectively. Patients with history of SUD were more likely to live without family members and have a history of depression, anxiety or PTSD than those without a SUD history; 78.3% vs 44.8% (p = 0.023) and 60.9% vs 20.7% (p = 0.004). In the year following diagnosis the mean percentage of missed appointments, number of ER visits, number of inpatient stays, and total length of inpatient stay for patients with history of SUD vs no history of SUD were: 19% vs 8% (p = 0.01), 3.7 vs 1.4 (p = 0.08), 2.6 vs 0.9 (p = 0.10), and 17.7 vs 5.9 days (p = 0.06) respectively. Conclusions: In this retrospective analysis of patients with localized NSCLC, those with a history of SUD had shorter time from diagnosis to last known contact without increased rates of loss-to-follow-up. They also had greater rates of depression, less family support, increased rates of missed appointments, more emergency room visits, increased hospitalizations, and increased total duration of inpatient stay in the year following their diagnosis.
Longitudinal tumor size and NLR as predictive factors of individual survival compared to their baseline values in patients with non-small cell lung cancer treated with durvalumab.
Authors: Zhudenkov Kirill , Gavrilov Sergey , Peskov Kirill , Helmlinger Gabriel , Aksenov Sergey 
Published: March 2020

e20047 Background: Our ability to accurately predict survival of patients with non-small cell lung cancer (NSCLC) while on treatment is limited. Prognostic markers such as stage and tumor size are well established, while neutrophil-to-lymphocytes ratio (NLR) and other hemogram measurements have recently been studied. Gain in prognostic accuracy of these markers when measured longitudinally has not been established. Methods: There were 679 NSCLC patients (Stage 3 or 4, ECOG PS 0 or 1) from clinical studies of durvalumab 10 mg/kg every two weeks (NCT02087423 and NCT01693562). We developed three models of overall survival (OS) all with ECOG as covariate: a Cox proportional hazards model with baseline tumor sum-of-longest-diameters (SLD) and NLR as covariates (COX); a joint model of OS and longitudinal SLD and baseline NLR (JM SLD); and a joint model of OS and longitudinal SLD and NLR (JM SLD&NLR). We compared prognostic accuracy of these markers measured longitudinally vs. at baseline, using predicted probability of OS at 12 months after start of durvalumab as a prognostic score. We evaluated predictive performance of the models using area under the receiver-operating characteristic curve (ROC AUC) describing trade-off between true and false positives (i.e., survival past 12 months). The AUCs were calculated for patients in the dataset using longitudinal data up to different cut-offs. Results: The AUC for all patients starting durvalumab using baseline ECOG, SLD and NLR was 0.73, while it decreased to 0.64 for patients surviving to 6 months, compared to 0.50 for noninformative models. The AUC using longitudinal information for SLD and NLR was larger the more longitudinal data was used for prediction and was 0.81 using 6 months’ worth of data. Conclusions: Using longitudinal information for SLD and NLR increased individual predictive performance of these markers compared to only baseline information in NSCLC patients. [Table: see text]
Report of four cases of pulmonary malignant tumors treated with SBRT using BODYFIX plus 4D-CBCT image guidance technique.
Authors: Wu Lei , Li Tao , Wang Qifeng 
Published: March 2020

e20050 Background: To monitor the range of motion in SBRT treatment of lung tumors by using BODYFIX combined with four-dimensional cone beam CT (4D-CBCT), and provide evidence for delineating the reasonable internal target area (ITV) of lung cancer, and observe the short-term outcom of treatment and treatment of complications. Methods: 4D-CT was used to locate CT scan, delineate the GTV of the tumor, make a simple radiation treatment planning, determine the treatment center point, and then use line accelerator 4D-CBCT to perform pre-SBRT treatment on 4 patients with lung malignant tumor. The system automatically reconstructs the image and matches the CT image of the treatment plan to obtain the placement error of the patient in the head and foot (SI), left and right (LR), and front and rear (AP) directions. The double registration technique is used to correct the correction first. Positioning error, the 4D-CBCT dynamic image is again registered with the target area, the range of motion within the tumor is observed, and the time-weighted 4D-CBCT image is transmitted back to the Monaco planning system to delineate the target area to accurately determine the range of the ITV. According to this target area, a radiation treatment planning was developed, GTV 20Gy/f, 1 to 3 fractions, and then 4D-CBCT scan was performed in each SBRT treatment to observe the range of tumor motion in real time. Results: 3 of the 4 patients the lung tumors were CR at 3 months after treatment, and 1 patient was SD. No serious complications occurred during the treatment or within 3 months after radiotherapy. Conclusions: The BODYFIX plus 4D-CBCT image can more accurately outline the ITV range of lung cancer. The patient is well tolerated and the short-term outcom is good.
The relative impact of patient and institutional rurality on lung cancer disparities.
Authors: Ray Meredith , Faris Nicholas Ryan , Derrick Anna , Smeltzer Matthew , Osarogiagbon Raymond U. 
Published: March 2020

e20052 Background: We quantified variation in stage specific, guideline concordant treatment and examined the interaction with rurality and overall survival (OS). Methods: We used tumor registry data for non-small cell lung cancer (NSCLC) patients at 5 institutions in the Mississippi Delta from 2011-2017, including patient demographics, clinical stage, treatment, and OS. We defined rurality by Rural-Urban Commuting Area codes, hospital and patient zip codes; based stage-stratified treatment on National Comprehensive Cancer Network guidelines; used Chi-squared and ANOVA F-tests to assess differences across institutions and logistic regression to assess associations between appropriate care, patient- and institution-level rurality. We used Log-rank tests to examine differences in OS and Cox proportional hazard regression to calculate hazard ratios (HR). Results: 6,259 patients were identified across 2 rural (n = 1255, 20%) and 3 metropolitan (metro) institutions (n = 5004, 80%). There were significant demographic and clinical differences between institutions: proportion of African-Americans (range: 6-37%, p < 0.001), uninsured (3-18%, p < 0.001), patient rurality (17-99%, p < 0.001), ‘no treatment’ rates (17-31%, p < 0.001). Metro patients or those treated at metro institutions were more likely to receive guideline-concordant treatment (odds ratio: 1.34, 95% CI [1.20 - 1.49]; 1.45 [1.28 - 1.65], respectively) than their rural counterparts and had improved OS (HR: 0.89; 95% CI [0.84 - 0.95]; 0.68 [0.63 - 0.72], respectively). They were also less likely to receive ‘no treatment’ (0.62 [0.55 - 0.71], p < 0.001; 0.51 [0.49 - 0.66], p < 0.001, respectively). Among patients with proper care, there were no patient-level rurality based OS differences (p = 0.2203) but those treated at metro institutions had better OS (p < 0.001). When stage-stratified, only advanced-stage patients treated at metro institutions had better survival (p < 0.001), no other differences in OS were detected for early or late-stage patients. Conclusions: Institution-level rurality had greater influence than patient-level rurality on receipt of guideline concordant care and OS. Appropriate care eliminated patient-level rurality OS disparities.