Prognostic utility of body composition parameters based on computed tomography analysis of advanced non-small cell lung cancer treated with immune checkpoint inhibitors.

OBJECTIVE: The purpose of this study was to evaluate the prognostic impact of body composition parameters based on computed tomography (CT) in patients with non-small cell lung cancer (NSCLC) who received ICI treatment. METHODS: This retrospective study analyzed the data from advanced NSCLC patients treated with ICI therapy between 2013 and 2019. We included patients with NSCLC who underwent baseline CT scans. The exclusion criteria included patients who received three or more lines of chemotherapy, those with insufficient clinical information, or those without treatment response evaluation. RESULTS: A total of 136 patients were enrolled. Among the volumetric body composition parameters, patients in the highest quartiles (Q2-4) of the visceral fat index (VFI) exhibited a higher response rate to ICI therapy than those in the lowest quartile (Q1) of VFI (Q1 vs. Q2-4: 18.2% vs. 43.1%, p = 0.012). Patients with a VFI in Q2-4 had significantly prolonged progression-free survival (PFS) and overall survival (OS) (PFS, Q1 vs. Q2-4: 3.0 months vs. 6.4 months, p = 0.043; OS, Q1 vs. Q2-4: 5.6 months vs. 16.3 months, p = 0.004). Kaplan-Meier analysis based on the VFI and visceral fat Hounsfield unit (HU) revealed that patients with VFI in Q1 and HU in Q2-4 had the worst prognosis. CONCLUSIONS: Visceral fat volume is significantly associated with treatment outcomes in ICI-treated patients with NSCLC. Moreover, fat quality may impact the treatment outcomes. This finding underscores the potential significance of both fat compartments and fat quality as prognostic indicators. CRITICAL RELEVANCE STATEMENT: Visceral fat volume is significantly associated with treatment outcomes in ICI-treated patients with non-small cell lung cancer. Moreover, fat quality may impact the treatment outcomes. This finding underscores the potential significance of both fat compartments and fat quality as prognostic indicators. KEY POINTS: • We found that visceral fat volume positively correlated with treatment response and survival in patients with non-small cell lung cancer receiving immune checkpoint inhibitors. • Additionally, a trend toward a negative correlation between visceral fat attenuation and survival was observed. • The findings highlight the prognostic utility of fat compartments and fat quality.

Small intestinal adenocarcinoma accompanied by lynch syndrome: A case report.

RATIONALE: Lynch syndrome is caused by germline mutations of DNA mismatch repair genes. A significant risk increase for several types of cancer is one of the characteristics of lynch syndrome. PATIENT CONCERNS: A 45-year-old female presented to the emergency department with abdominal pain that had persisted for a month. DIAGNOSES: The abdominal and pelvic computed tomography scan showed edematous and thickening of the proximal small bowel wall, as well as dilatation of the proximal bowel and stomach. INTERVENTIONS: Tumor resection of the small bowel was performed, and adenocarcinoma was confirmed pathologically. Microsatellite instability was also confirmed. OUTCOMES: Postoperative imaging revealed soft tissue lesions with potential for tumor seeding. Two months after the first surgery, a secondary surgery was performed as a result of cancer recurrence. The patient received chemotherapy with capecitabine. The latest computed tomography scan, performed 19 months after the cessation of chemotherapy, did not show any recurrence. LESSONS: In the rare incidence of small bowel cancer genetic mutation testing and detailed family history should be actively considered.

RCMVis: A Visual Analytics System for Route Choice Modeling.

We present RCMVis, a visual analytics system to support interactive Route Choice Modeling analysis. It aims to model which characteristics of routes, such as distance and the number of traffic lights, affect travelers' route choice behaviors and how much they affect the choice during their trips. Through close collaboration with domain experts, we designed a visual analytics framework for Route Choice Modeling. The framework supports three interactive analysis stages: exploration, modeling, and reasoning. In the exploration stage, we help analysts interactively explore trip data from multiple origin-destination (OD) pairs and choose a subset of data they want to focus on. To this end, we provide coordinated multiple OD views with different foci that allow analysts to inspect, rank, and compare OD pairs in terms of their multidimensional attributes. In the modeling stage, we integrate a k-medoids clustering method and a path-size logit model into our system to enable analysts to model route choice behaviors from trips with support for feature selection, hyperparameter tuning, and model comparison. Finally, in the reasoning stage, we help analysts rationalize and refine the model by selectively inspecting the trips that strongly support the modeling result. For evaluation, we conducted a case study and interviews with domain experts. The domain experts discovered unexpected insights from numerous modeling results, allowing them to explore the hyperparameter space more effectively to gain better results. In addition, they gained OD- and road-level insights into which data mainly supported the modeling result, enabling further discussion of the model.

SizePairs: Achieving Stable and Balanced Temporal Treemaps using Hierarchical Size-based Pairing.

We present SizePairs, a new technique to create stable and balanced treemap layouts that visualize values changing over time in hierarchical data. To achieve an overall high-quality result across all time steps in terms of stability and aspect ratio, SizePairs employs a new hierarchical size-based pairing algorithm that recursively pairs two nodes that complement their size changes over time and have similar sizes. SizePairs maximizes the visual quality and stability by optimizing the splitting orientation of each internal node and flipping leaf nodes, if necessary. We also present a comprehensive comparison of SizePairs against the state-of-the-art treemaps developed for visualizing time-dependent data. SizePairs outperforms existing techniques in both visual quality and stability, while being faster than the local moves technique.

Green and Sustainable Hot Melt Adhesive (HMA) Based on Polyhydroxyalkanoate (PHA) and Silanized Cellulose Nanofibers (SCNFs).

Polyhydroxyalkanoate (PHA), with a long chain length and high poly(4-hydroxybutyric acid) (P4HB) ratio, can be used as a base polymer for eco-friendly and biodegradable adhesives owing to its high elasticity, elongation at break, flexibility, and processability; however, its molecular structures must be adjusted for adhesive applications. In this study, surface-modified cellulose nanofibers (CNFs) were used as a hydrophobic additive for the PHA-based adhesive. For the surface modification of CNFs, double silanization using tetraethyl orthosilicate (TEOS) and methyltrimethoxysilane (MTMS) was performed, and the thermal and structural properties were evaluated. The hydrophobicity of the TEOS- and MTMS-treated CNFs (TMCNFs) was confirmed by FT-IR and water contact angle analysis, with hydrophobic CNFs well dispersed in the PHA. The PHA-CNFs composite was prepared with TMCNFs, and its morphological analysis verified the good dispersion of TMCNFs in the PHA. The tensile strength of the composite was enhanced when 10% TMCNFs were added; however, the viscosity decreased as the TMCNFs acted as a thixotropic agent. Adding TMCNFs to PHA enhanced the flowability and infiltration ability of the PHA-TMCNFs-based adhesive, and an increase in the loss tangent (Tan δ) and adjustment of viscosity without reducing the adhesive strength was also observed. These changes in properties can improve the flowability and dispersibility of the PHA-TMCNFs adhesive on a rough adhesive surface at low stress. Thus, it is expected that double-silanized CNFs effectively improve their interfacial adhesion in PHA and the adhesive properties of the PHA-CNFs composites, which can be utilized for more suitable adhesive applications.

Human zoonotic infectious disease caused by Streptococcus equi subsp. zooepidemicus.

Streptococcus equi subsp. zooepidemicus (SEZ) is a highly contagious infectious organism that causes disease in horses. SEZ is seldom isolated from humans; however, zoonotic infections are occasionally reported in individuals exposed to horses and other livestock. Herein, we report three human cases of SEZ in individuals, one with direct horse contact and two among individuals who had eaten raw horse meat. The phylogenetic tree showed that the genotypes of SEZ isolates from two of the cases on Jeju Island, South Korea, were similar to those of isolates from the United Kingdom and the United States of America.

Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets.

We present Joint t-Stochastic Neighbor Embedding (Joint t-SNE), a technique to generate comparable projections of multiple high-dimensional datasets. Although t-SNE has been widely employed to visualize high-dimensional datasets from various domains, it is limited to projecting a single dataset. When a series of high-dimensional datasets, such as datasets changing over time, is projected independently using t-SNE, misaligned layouts are obtained. Even items with identical features across datasets are projected to different locations, making the technique unsuitable for comparison tasks. To tackle this problem, we introduce edge similarity, which captures the similarities between two adjacent time frames based on the Graphlet Frequency Distribution (GFD). We then integrate a novel loss term into the t-SNE loss function, which we call vector constraints, to preserve the vectors between projected points across the projections, allowing these points to serve as visual landmarks for direct comparisons between projections. Using synthetic datasets whose ground-truth structures are known, we show that Joint t-SNE outperforms existing techniques, including Dynamic t-SNE, in terms of local coherence error, Kullback-Leibler divergence, and neighborhood preservation. We also showcase a real-world use case to visualize and compare the activation of different layers of a neural network.

Measuring and Explaining the Inter-Cluster Reliability of Multidimensional Projections.

We propose Steadiness and Cohesiveness, two novel metrics to measure the inter-cluster reliability of multidimensional projection (MDP), specifically how well the inter-cluster structures are preserved between the original high-dimensional space and the low-dimensional projection space. Measuring inter-cluster reliability is crucial as it directly affects how well inter-cluster tasks (e.g., identifying cluster relationships in the original space from a projected view) can be conducted; however, despite the importance of inter-cluster tasks, we found that previous metrics, such as Trustworthiness and Continuity, fail to measure inter-cluster reliability. Our metrics consider two aspects of the inter-cluster reliability: Steadiness measures the extent to which clusters in the projected space form clusters in the original space, and Cohesiveness measures the opposite. They extract random clusters with arbitrary shapes and positions in one space and evaluate how much the clusters are stretched or dispersed in the other space. Furthermore, our metrics can quantify pointwise distortions, allowing for the visualization of inter-cluster reliability in a projection, which we call a reliability map. Through quantitative experiments, we verify that our metrics precisely capture the distortions that harm inter-cluster reliability while previous metrics have difficulty capturing the distortions. A case study also demonstrates that our metrics and the reliability map 1) support users in selecting the proper projection techniques or hyperparameters and 2) prevent misinterpretation while performing inter-cluster tasks, thus allow an adequate identification of inter-cluster structure.

Changes in Mechanical Properties of Polyhydroxyalkanoate with Double Silanized Cellulose Nanocrystals Using Different Organosiloxanes.

Polyhydroxyalkanoate (PHA) is a biodegradable plastic with great potential for tackling plastic waste and marine pollution issues, but its commercial applications have been limited due to its poor processability. In this study, surface-modified cellulose nanocrystals were used to improve the mechanical properties of PHA composites produced via a melt-extrusion process. Double silanization was conducted to obtain hydrophobically treated CNC-based fillers, using tetraethyl orthosilicate (TEOS) and methyltrimethoxysilane (MTMS). The morphology, particle size distributions, and surface characteristics of the silanized CNCs and their compatibility with a PHA polymer matrix differed by the organosiloxane treatment and drying method. It was confirmed that the double silanized CNCs had hydrophobic surface characteristics and narrow particle size distributions, and thereby showed excellent dispersibility in a PHA matrix. Adding hydrophobically treated CNCs to form a PHA composite, the elongation at break of the PHA composites was improved up to 301%, with little reduction of Young's modulus, compared to pure PHA. Seemingly, the double silanized CNCs added played a similar role to a nucleation agent in the PHA composite. It is expected that such high ductility can improve the mechanical properties of PHA composites, making them more suitable for commercial applications.

Nobiletin Exhibits Neuroprotective Effects against Mitochondrial Complex I Inhibition via Regulating Apoptotic Signaling.

Nobiletin, a polymethoxylated flavonoid found in citrus, has been studied because of its modulatory functions in cellular signaling cascades, and effects to prevent mitochondrial calcium overload and neuronal cell death. Particularly, we previously reported that nobiletin induced changes in the mitochondrial membrane potential through K+ channel regulation, suggesting that nobiletin might exert neuroprotective effects via regulating mitochondrial functions associated with the electron transport chain (ETC) system. This study investigated whether nobiletin regulated mitochondrial dysfunction mediated by ETC system downregulation by inhibiting complex I (CI) and complex III (CIII) in pure mitochondria and the cortical neurons of rats. The results showed that nobiletin significantly reduced mitochondrial reactive oxygen species (ROS) production, inhibited apoptotic signaling, enhanced ATP production and then restored neuronal viability under conditions of CI inhibition, but not CIII inhibition. These effects were attributed to the downregulation of translocation of apoptosis-induced factor (AIF), and the upregulation of CI activity and the expression of antioxidant enzymes such as Nrf2 and HO-1. Together with our previous study, these results indicate that the neuroprotective effects of nobiletin under mitochondrial dysfunction may be associated with its function to activate antioxidant signaling cascades. Our findings suggest the possibility that nobiletin has therapeutic potential in treating oxidative neurological and neurodegenerative diseases mediated by mitochondrial dysfunction.

ProReveal: Progressive Visual Analytics With Safeguards.

We present a new visual exploration concept-Progressive Visual Analytics with Safeguards-that helps people manage the uncertainty arising from progressive data exploration. Despite its potential benefits, intermediate knowledge from progressive analytics can be incorrect due to various machine and human factors, such as a sampling bias or misinterpretation of uncertainty. To alleviate this problem, we introduce PVA-Guards, safeguards people can leave on uncertain intermediate knowledge that needs to be verified, and derive seven PVA-Guards based on previous visualization task taxonomies. PVA-Guards provide a means of ensuring the correctness of the conclusion and understanding the reason when intermediate knowledge becomes invalid. We also present ProReveal, a proof-of-concept system designed and developed to integrate the seven safeguards into progressive data exploration. Finally, we report a user study with 14 participants, which shows people voluntarily employed PVA-Guards to safeguard their findings and ProReveal's PVA-Guard view provides an overview of uncertain intermediate knowledge. We believe our new concept can also offer better consistency in progressive data exploration, alleviating people's heterogeneous interpretation of uncertainty.

Comparative Layouts Revisited: Design Space, Guidelines, and Future Directions.

We present a systematic review on three comparative layouts-juxtaposition, superposition, and explicit-encoding-which are information visualization (InfoVis) layouts designed to support comparison tasks. For the last decade, these layouts have served as fundamental idioms in designing many visualization systems. However, we found that the layouts have been used with inconsistent terms and confusion, and the lessons from previous studies are fragmented. The goal of our research is to distill the results from previous studies into a consistent and reusable framework. We review 127 research papers, including 15 papers with quantitative user studies, which employed comparative layouts. We first alleviate the ambiguous boundaries in the design space of comparative layouts by suggesting lucid terminology (e.g., chart-wise and item-wise juxtaposition). We then identify the diverse aspects of comparative layouts, such as the advantages and concerns of using each layout in the real-world scenarios and researchers' approaches to overcome the concerns. Building our knowledge on top of the initial insights gained from the Gleicher et al.'s survey [19], we elaborate on relevant empirical evidence that we distilled from our survey (e.g., the actual effectiveness of the layouts in different study settings) and identify novel facets that the original work did not cover (e.g., the familiarity of the layouts to people). Finally, we show the consistent and contradictory results on the performance of comparative layouts and offer practical implications for using the layouts by suggesting trade-offs and seven actionable guidelines.

Diffuse alveolar hemorrhage from metastatic cardiac angiosarcoma of the lung successfully treated with paclitaxel chemotherapy: A case report and brief literature review.

Diffuse alveolar hemorrhage (DAH) is a life-threatening syndrome caused by various etiologies. DAH has rarely been reported to be associated with metastatic angiosarcoma. However, due to the rarity of complications, it may not be well-recognized by most clinicians. Herein, we report the case of a 70-year-old man with newly diagnosed metastatic cardiac angiosarcoma presenting with DAH. After an immediate bronchoalveolar lavage study and bronchoscopic biopsy, the patient was successfully treated with paclitaxel chemotherapy. Although most patients with this phenomenon have an extremely grave prognosis in previous literature, our experience showed that appropriate evaluation and treatment may be beneficial.

Incorporating hematopoietic stem-cell transplantation after second-line carfilzomib-lenalidomide-dexamethasone (KRd).

BACKGROUND: Traditionally believed to be an integral part of multiple myeloma (MM) treatment, the role of hematopoietic stem-cell transplantation (HSCT) is being challenged. As such, we sought to evaluate the impact of HSCT in the era of novel agents. METHODS: A multicenter, retrospective, longitudinal cohort study was carried out between January 2016 and December 2018. A total of 55 patients who received VTD (bortezomib-thalidomide-dexamethasone) as first-line treatment and KRd (carfilzomib-lenalidomide-dexamethasone) as second-line treatment were analyzed for outcomes. RESULTS: The enrolled patients were divided into Group 1, defined as those who continued KRd treatment until progression (n = 41), versus Group 2, defined as those who underwent HSCT after a certain number of cycles of KRd (n = 14). Both groups showed a generally favorable response to KRd, with overall response rate (ORR) of 87.9% and clinical benefit rate of 92.8% after a median of seven cycles in Group 1, and ORR 92.8% and clinical benefit rate 100% after median of five cycles in Group 2. However, significantly poorer progression-free survival (PFS) (p = 0.004) was observed in Group 1 (median 12 months) compared with Group 2 (median not reached). Multivariate analyses identified HSCT after KRd as potential risk factors associated with PFS. Also, in Group 1, bortezomib refractoriness was associated with significantly shorter PFS compared with those who were responsive (median 12 months versus 14 months, respectively, p = 0.039). CONCLUSIONS: In conclusion, even with the advent of novel agents, HSCT still remains a valuable treatment modality with additive efficacy.

L-Ascorbic Acid Inhibits Breast Cancer Growth by Inducing IRE/JNK/CHOP-Related Endoplasmic Reticulum Stress-Mediated p62/SQSTM1 Accumulation in the Nucleus.

Anticancer effects of L-ascorbic acid (Vitamin C, L-AA) have been reported in various types of cancers. L-AA intake reduces breast cancer recurrence and mortality; however, the role of L-AA in the treatment of breast cancer remains poorly understood. In this study, we investigated the effect and mechanism action of L-AA on breast cancer growth. L-AA inhibited the growth of breast cancer cells by inducing apoptotic cell death at the evaluated treatment concentrations without affecting normal cells. Moreover, L-AA induces autophagosome formation via regulation of mammalian target of rapamycin (mTOR), Beclin1, and autophagy-related genes (ATGs) and increased autophagic flux. Notably, we observed that L-AA increased p62/SQSTM1 (sequestosome 1) protein levels. Accumulation of p62 protein in cancer cells in response to stress has been reported, but its role in cancer regulation remains controversial. Here, we demonstrated that L-AA-induced p62 accumulation is related to L-AA-induced breast cancer growth inhibition. Furthermore, L-AA induced endoplasmic reticulum (ER) stress via the IRE-JNK-CHOP (inositol-requiring endonuclease-c-Jun N-terminal kinase-C/EBP homologous protein) signaling pathways, which increased the nuclear levels of p62/SQSTM1. These findings provide evidence that L-AA-induced ER stress could be crucial for p62 accumulation-dependent cell death, and L-AA can be useful in breast cancer treatment.

PANENE: A Progressive Algorithm for Indexing and Querying Approximate k-Nearest Neighbors.

We present PANENE, a progressive algorithm for approximate nearest neighbor indexing and querying. Although the use of k-nearest neighbor (KNN) libraries is common in many data analysis methods, most KNN algorithms can only be queried when the whole dataset has been indexed, i.e., they are not online. Even the few online implementations are not progressive in the sense that the time to index incoming data is not bounded and cannot satisfy the latency requirements of progressive systems. This long latency has significantly limited the use of many machine learning methods, such as t-SNE, in interactive visual analytics. PANENE is a novel algorithm for Progressive Approximate k-NEarest NEighbors, enabling fast KNN queries while continuously indexing new batches of data. Following the progressive computation paradigm, PANENE operations can be bounded in time, allowing analysts to access running results within an interactive latency. PANENE can also incrementally build and maintain a cache data structure, a KNN lookup table, to enable constant-time lookups for KNN queries. Finally, we present three progressive applications of PANENE, such as regression, density estimation, and responsive t-SNE, opening up new opportunities to use complex algorithms in interactive systems.

Daratumumab Monotherapy in Heavily Pretreated Asian Patients With Relapsed and Refractory Multiple Myeloma: A Real-world Experience.

BACKGROUND/AIM: Daratumumab is a promising novel agent for relapsed/refractory multiple myeloma (RRMM). However, there are limited data on its efficacy and toxicity profiles in real-world patients, especially in the Asian population. PATIENTS AND METHODS: This was a multicenter, retrospective, longitudinal cohort study set between January 2017 and April 2019. We collected and analyzed clinical and survival data of 21 patients treated with daratumumab monotherapy. All patients were previously exposed to proteasome inhibitors and immunomodulatory drugs. RESULTS: The overall response rate was 42.1%, including one complete remission (4.8%) and three very good partial responses (14.3%). The cycles of daratumumab delivered were three (range=1-10 cycles) and the median progression-free survival was 6 months, while the overall survival was not reached. Infusion reaction was observed in nine patients (42.9%), and one discontinued permanently. Fatigue was the most common adverse event (52.4%), and there were five cases of documented infection during daratumumab treatment, two of them leading to the death of the patient. CONCLUSION: Daratumumab monotherapy showed fairly promising activity with modest tolerance in heavily treated Asian RRMM patients.

Capecitabine Plus Oxaliplatin Combination Therapy for Basal Cell Carcinoma.

No effective systemic chemotherapy is well-established in basal cell carcinoma. We report a case with three simultaneous malignancies: colon cancer, basal cell carcinoma, and smoldering multiple myeloma. The patient was treated with capecitabine and oxaliplatin after surgery for colon cancer. Surprisingly, he achieved a complete response for basal cell carcinoma. This is the first report of this chemotherapy regimen in basal cell carcinoma. This finding suggests that combination capecitabine and oxaliplatin can be a treatment option for patients unable to receive local therapy.

A Declarative Rendering Model for Multiclass Density Maps.

Multiclass maps are scatterplots, multidimensional projections, or thematic geographic maps where data points have a categorical attribute in addition to two quantitative attributes. This categorical attribute is often rendered using shape or color, which does not scale when overplotting occurs. When the number of data points increases, multiclass maps must resort to data aggregation to remain readable. We present multiclass density maps: multiple 2D histograms computed for each of the category values. Multiclass density maps are meant as a building block to improve the expressiveness and scalability of multiclass map visualization. In this article, we first present a short survey of aggregated multiclass maps, mainly from cartography. We then introduce a declarative model-a simple yet expressive JSON grammar associated with visual semantics-that specifies a wide design space of visualizations for multiclass density maps. Our declarative model is expressive and can be efficiently implemented in visualization front-ends such as modern web browsers. Furthermore, it can be reconfigured dynamically to support data exploration tasks without recomputing the raw data. Finally, we demonstrate how our model can be used to reproduce examples from the past and support exploring data at scale.

Efficacy of Pemetrexed-based Chemotherapy in Comparison to Non-Pemetrexed-based Chemotherapy in Advanced, ALK+ Non-Small Cell Lung Cancer.

PURPOSE: Previous retrospective studies suggest that anaplastic lymphoma kinase (ALK) mutation-positive (ALK+) non-small cell lung cancer (NSCLC) patients are sensitive to pemetrexed. To determine its efficacy, we retrospectively evaluated clinical outcomes of pemetrexed-based chemotherapy in patients with ALK+ NSCLC. MATERIALS AND METHODS: We identified 126 patients with advanced, ALK+ NSCLC who received first-line cytotoxic chemotherapy. We compared response, progression-free survival (PFS), and overall survival (OS) rates according to chemotherapy regimens. Furthermore, we evaluated intracranial time to tumor progression (TTP) and proportion of ALK+ cells as prognostic factors. RESULTS: Forty-eight patients received pemetrexed-based chemotherapy, while 78 received other regimens as first-line treatment. The pemetrexed-based chemotherapy group showed superior overall response (44.7% vs. 14.3%, p<0.001) and disease control (85.1% vs. 62.3%, p=0.008) rates. The pemetrexed-based chemotherapy group also exhibited longer PFS (6.6 months vs. 3.8 months, p<0.001); OS rates were not significantly different. The lack of exposure to second-generation ALK inhibitors and intracranial metastasis on initial diagnosis were independent negative prognostic factors of OS. Intracranial TTP was similar between the treatment groups (32.7 months vs. 35.7 months, p=0.733). Patients who harbored a greater number of ALK+ tumor cells (≥70%) showed prolonged OS on univariate analysis (not reached vs. 44.8 months, p=0.041), but not on multivariate analysis (hazard ratio: 0.19, 95% confidence interval: 0.03-1.42; p=0.106). CONCLUSION: Pemetrexed-based regimens may prolong PFS in patients with ALK+ NSCLC as a first-line treatment, but are not associated with prolonged OS. Exposure to second-generation ALK inhibitors may improve OS rates in patients with ALK+ NSCLC.