DSANet: Dynamic and Structure-Aware GCN for Sparse and Incomplete Point Cloud Learning.

Learning 3-D structures from incomplete point clouds with extreme sparsity and random distributions is a challenge since it is difficult to infer topological connectivity and structural details from fragmentary representations. Missing large portions of informative structures further aggravates this problem. To overcome this, a novel graph convolutional network (GCN) called dynamic and structure-aware NETwork (DSANet) is presented in this article. This framework is formulated based on a pyramidic auto-encoder (AE) architecture to address accurate structure reconstruction on the sparse and incomplete point clouds. A PointNet-like neural network is applied as the encoder to efficiently aggregate the global representations of coarse point clouds. On the decoder side, we design a dynamic graph learning module with a structure-aware attention (SAA) to take advantage of the topology relationships maintained in the dynamic latent graph. Relying on gradually unfolding the extracted representation into a sequence of graphs, DSANet is able to reconstruct complicated point clouds with rich and descriptive details. To associate analogous structure awareness with semantic estimation, we further propose a mechanism, called structure similarity assessment (SSA). This method allows our model to surmise semantic homogeneity in an unsupervised manner. Finally, we optimize the proposed model by minimizing a new distortion-aware objective end-to-end. Extensive qualitative and quantitative experiments demonstrate the impressive performance of our model in reconstructing unbroken 3-D shapes from deficient point clouds and preserving semantic relationships among different regional structures.

A quantitative evaluation of the deep learning model of segmentation and measurement of cervical spine MRI in healthy adults.

PURPOSE: To evaluate the 3D U-Net model for automatic segmentation and measurement of cervical spine structures using magnetic resonance (MR) images of healthy adults. MATERIALS AND METHODS: MR images of the cervical spine from 160 healthy adults were collected retrospectively. A previously constructed deep-learning model was used to automatically segment anatomical structures. Segmentation and localization results were checked by experienced radiologists. Pearson's correlation analyses were conducted to examine relationships between patient and image parameters. RESULTS: No measurement was significantly correlated with age or sex. The mean values of the areas of the subarachnoid space and spinal cord from the C2/3 (cervical spine 2-3) to C6/7 intervertebral disc levels were 102.85-358.12 mm2 and 53.71-110.32 mm2 , respectively. The ratios of the areas of the spinal cord to the subarachnoid space were 0.25-0.68. The transverse and anterior-posterior diameters of the subarachnoid space were 14.77-26.56 mm and 7.38-17.58 mm, respectively. The transverse and anterior-posterior diameters of the spinal cord were 9.11-16.02 mm and 5.47-10.12 mm, respectively. CONCLUSION: A deep learning model based on 3D U-Net automatically segmented and performed measurements on cervical spine MR images from healthy adults, paving the way for quantitative diagnosis models for spinal cord diseases.

Comparative Study of the Diagnostic Value of Zero-Echo-Time Magnetic Resonance Angiography With Time-of-Flight Magnetic Resonance Angiography for Intracranial Aneurysm.

OBJECTIVE: Intracranial aneurysm (IAN) is a class of cerebrovascular diseases with a serious threat to patients, and an accurate diagnosis of IAN is very important for both selection of the appropriate therapy and prediction of the prognosis. This study aimed to evaluate the diagnostic values of zero-echo-time magnetic resonance angiography (ZTE-MRA) and time-of-flight magnetic resonance angiography (TOF-MRA) in patients with IAN. METHODS: Digital subtraction angiography, ZTE-MRA, and TOF-MRA were performed in 18 patients diagnosed with IAN. The images of ZTE-MRA and TOF-MRA were compared for image quality, qualitative diagnosis, detailed diagnosis, number of thrombi, and residual aneurysm lumen, with digital subtraction angiography as the reference. RESULTS: Zero-echo-time MRA and TOF-MRA did not show a significant difference in image quality or detailed information (including aneurysm size, growth direction, and angle with the aneurysm-carrying vessel) ( P > 0.05). However, ZTE-MRA showed advantages over TOF-MRA in terms of qualitative diagnosis (sensitivity and specificity), intra-aneurismal thrombus detection, and residual aneurysm lumen detection after embolization ( P < 0.05). CONCLUSIONS: Compared with TOF-MRA, ZTE-MRA showed greater diagnostic value for IAN patients in terms of qualitative diagnosis, as well as the detection of intra-aneurysm thrombi and residual aneurysm lumen after embolization.

Preparation of Taraxacum kok-saghyz Rubber and Biofuel Ethanol Simultaneously by the Yeast Fermentation Process.

Taraxacum kok-saghyz(TKS) rubber is considered the most ideal alternative source of natural rubber (NR). Extracting rubber from TKS with high quality, low cost, and low pollution is the basis of commercial development. The TKS roots were subjected to morphological observation and detailed compositional analysis. Scanning electron microscopy (SEM) images confirm that rubber filaments are physically entangled with plant tissues due to differences in molecular polarity. Compared with the traditional solvent TKS rubber extraction process, a new rubber extraction process developed in this study, namely, the microbial extraction (″ME″) process, is less harmful to the environment and lower in cost. The ″ME″ process is divided into three steps: dilute acid pretreatment process, enzyme degradation process, and fermentation process. After each step is completed, the purity of TKS rubber will gradually increase from 84.8% to 93.8 to 95.5%. The TKS rubber finally obtained fully meets the requirements of the traditional rubber industry, especially the tire industry. Besides, the yield of biofuel ethanol, a by-product of cellulose fermentation, reaches 2.05 g/100 g of TKS roots (dry weight), which can effectively reduce the production cost of TKS rubber. In the rubber extraction process, microorganisms have little effect on the quality of TKS rubber. The results show that the molecular weight and chemical structure of TKS rubber is very close to NR, so the ″ME″ process can be used as a new method for large-scale extraction of TKS rubber.

Activation of the EGFR/PI3K/AKT pathway limits the efficacy of trametinib treatment in head and neck cancer.

Blocking the mitogen-activated protein kinase (MAPK) pathway with the MEK1/2 inhibitor trametinib has produced promising results in patients with head and neck squamous cell carcinoma (HNSCC). In the current study, we showed that trametinib treatment leads to overexpression and activation of the epidermal growth factor receptor (EGFR) in HNSCC cell lines and patient-derived xenografts. Knockdown of EGFR improved trametinib treatment efficacy both in vitro and in vivo. Mechanistically, we demonstrated that trametinib-induced EGFR overexpression hyperactivates the phosphatidylinositol 3-kinase (PI3K)/AKT pathway. In vitro, blocking the PI3K pathway with GDC-0941 (pictilisib), or BYL719 (alpelisib), prevented AKT pathway hyperactivation and enhanced the efficacy of trametinib in a synergistic manner. In vivo, a combination of trametinib and BYL719 showed superior antitumor efficacy vs. the single agents, leading to tumor growth arrest. We confirmed our findings in a syngeneic murine head and neck cancer cell line in vitro and in vivo. Taken together, our findings show that trametinib treatment induces hyperactivation of EGFR/PI3K/AKT; thus, blocking of the EGFR/PI3K pathway is required to improve trametinib efficacy in HNSCC.

Radiomics model based on intravoxel incoherent motion and diffusion kurtosis imaging for predicting histopathological grade and Ki-67 expression level of soft tissue sarcomas.

BACKGROUND: Accurate identification of the histopathological grade and the Ki-67 expression level is important in clinical cases of soft tissue sarcomas (STSs). PURPOSE: To explore the feasibility of a radiomics model based on intravoxel incoherent motion (IVIM) magnetic resonance imaging (MRI) and diffusion kurtosis imaging (DKI) MRI parameter maps in predicting the histopathological grade and Ki-67 expression level of STSs. MATERIAL AND METHODS: In total, 42 patients diagnosed with STSs between May 2018 and January 2020 were selected. The MADC software in Functool of GE ADW 4.7 workstation was used to obtain standard apparent diffusion coefficient (ADC), D, D*, f, mean diffusivity, and mean kurtosis (MK). The histopathological grade and Ki-67 expression level of STSs were identified. The radiomics features of IVIM and DKI parameter maps were used as the dataset. The area under the receiver operating characteristic curve (AUC) and F1-score were calculated. RESULTS: D-SVM achieved the best diagnostic performance for histopathological grade. The AUC in the validation cohort was 0.88 (sensitivity: 0.75 [low level] and 0.83 [high level]; specificity: 0.83 [low level] and 0.75 [high level]; F1-score: 0.75 [low level] and 0.83 [high level]). MK-SVM achieved the best diagnostic performance for Ki-67 expression level. The AUC in the validation cohort was 0.83 (sensitivity: 0.83 [low level] and 0.50 [high level; specificity: 0.50 [low level] and 0.83 [high level]; F1-score: 0.77 [low level] and 0.57 [high level]). CONCLUSION: The proposed radiomics classifier could predict the pathological grade of STSs and the Ki-67 expression level in STSs.

NCAPG promotes the oncogenesis and progression of non-small cell lung cancer cells through upregulating LGALS1 expression.

BACKGROUND: Numerous common oncogenic driver events have been confirmed in non-small cell lung cancer (NSCLC). Although targeted therapy has revolutionized NSCLC treatment, some patients still do not respond. NCAPG, also known as non-SMC condensin I complex subunit G, was positively associated with proliferation and migration in several tumor types. METHODS: We used transcriptional sequencing and TCGA database analysis to identify NCAPG as a new therapeutic target for NSCLC. The oncogenic roles of NCAPG in NSCLC tumor growth and metastasis were detected in vitro and in vivo. Ncapg+/+ or Ncapg+/- mice with urethane treatment were analyzed for oncogenesis of NSCLC. RESULTS: We investigated NCAPG as a new oncogenic driver which promoted NSCLC tumorigenesis and progression. We used transcriptome sequencing and the Cancer Genome Atlas (TCGA) database analysis to screen and found that NCAPG was negatively correlated with NSCLC survival. Using immunohistochemistry, we demonstrated that NCAPG overexpression was an independent risk factor for NSCLC survival. Functionally, NCAPG knockdown inhibited proliferation, migration, and invasion of NSCLC cells in vitro and in vivo. We exposed wildtype or Ncapg+/- mice to urethane and discovered that urethane-induced lung tumors were reduced in Ncapg+/- mice. Mechanistically, the function of NCAPG in promoting initiation and progression of NSCLC was closely related to LGALS1, which was also upregulated in NSCLC and might interact directly with NCAPG. CONCLUSIONS: This study indicates that NCAPG is one of the essential factors for NSCLC oncogenesis and progression, providing a new target for prognosis prediction and treatment of NSCLC.

Global, regional, and national burdens of hip osteoarthritis from 1990 to 2019: estimates from the 2019 Global Burden of Disease Study.

BACKGROUND: Hip osteoarthritis is a common disabling condition of the hip joint and is associated with a substantial health burden. We assessed the epidemiological patterns of hip osteoarthritis from 1990 to 2019 by sex, age, and socio-demographic index (SDI). METHODS: Age-standardized rates (ASRs) were obtained for the incidence and disability-adjusted life years (DALYs) of hip osteoarthritis from 1990 to 2019 for 21 regions, encompassing a total of 204 countries and territories. The estimated annual percentage changes (EAPCs) of ASRs were calculated to evaluate the trends in the incidence and DALYs of hip osteoarthritis over these 30 years. RESULTS: Globally, from 1990 to 2019, the age-standardized incidence rate (ASIR) of hip osteoarthritis increased from 17.02 per 100,000 persons to 18.70 per 100,000 persons, with an upward trend in the EAPC of 0.32 (0.29-0.34), whereas the age-standardized DALY rate increased from 11.54 per 100,000 persons to 12.57 per 100,000 persons, with an EAPC of 0.29 (0.27-0.32). In 2019, the EAPCs of the ASIR and age-standardized DALY rate of hip osteoarthritis were positively associated with the SDI of hip osteoarthritis. In 1990 and 2019, the incidence of hip osteoarthritis was unimodally distributed across different age groups, with a peak incidence in the 60-64-year-old age group, whereas the DALYs increased with age. CONCLUSIONS: The incidence and DALYs of hip osteoarthritis have been increasing globally. The EAPCs of the ASIR and age-standardized DALY rate were particularly significant in developed regions and varied across nations and regions, indicating the urgent need for governments and medical institutions to increase the awareness regarding risk factors, consequences of hip osteoarthritis.

SG-GAN: Adversarial Self-Attention GCN for Point Cloud Topological Parts Generation.

Point clouds are fundamental in the representation of 3D objects. However, they can also be highly unstructured and irregular. This makes it difficult to directly extend 2D generative models to three-dimensional space. In this article, we cast the problem of point cloud generation as a topological representation learning problem. In order to capture the representative features of 3D shapes in the latent space, we propose a hierarchical mixture model that integrates self-attention with an inference tree structure for constructing a point cloud generator. Based on this, we design a novel Generative Adversarial Network (GAN) architecture that is capable of generating recognizable point clouds in an unsupervised manner. The proposed adversarial framework (SG-GAN) relies on self-attention mechanism and Graph Convolution Network (GCN) to hierarchically infer the latent topology of 3D shapes. Embedding and transferring the global topology information in a tree framework allows our model to capture and enhance the structural connectivity. Furthermore, the proposed architecture endows our model with partially generating 3D structures. Finally, we propose two gradient penalty methods to stabilize the training of SG-GAN and overcome the possible mode collapse of GAN networks. To demonstrate the performance of our model, we present both quantitative and qualitative evaluations and show that SG-GAN is more efficient in training and it exceeds the state-of-the-art in 3D point cloud generation.

Organoids in Lung Cancer Management.

Lung cancer is a complex milieu of genomically altered cancer cells, a diverse collection of differentiated cells and nonneoplastic stroma. Lung cancer organoids is a three-dimensional structure grown from patient cancer tissue that could mimic in vivo complex behavior and cellular architecture of the cancer. Furthermore, the genomic alterations of the primary lung tumor is captured ex vivo. Lung cancer organoids have become an important preclinical model for oncology studies in recent years. It could be used to model the development of lung cancer, investigate the process of tumorigenesis, and also study the signaling pathways. The organoids could also be a platform to perform drug screening and biomarker validation of lung cancer, providing a promising prediction of patient-specific drug response. In this review, we described how lung cancer organoids have opened new avenues for translating basic cancer research into clinical therapy and discussed the latest and future developments in organoid technology, which could be further applied in lung cancer organoids research.

HSGAN: Hierarchical Graph Learning for Point Cloud Generation.

Point clouds are the most general data representations of real and abstract objects, and have a wide variety of applications in many science and engineering fields. Point clouds also provide the most scalable multi-resolution composition for geometric structures. Although point cloud learning has shown remarkable results in shape estimation and semantic segmentation, the unsupervised generation of 3D object parts still pose significant challenges in the 3D shape understanding problem. We address this problem by proposing a novel Generative Adversarial Network (GAN), named HSGAN, or Hierarchical Self-Attention GAN, with remarkable properties for 3D shape generation. Our generative model takes a random code and hierarchically transforms it into a representation graph by incorporating both Graph Convolution Network (GCN) and self-attention. With embedding the global graph topology in shape generation, the proposed model takes advantage of the latent topological information to fully construct the geometry of 3D object shapes. Different from the existing generative pipelines, our deep learning architecture articulates three significant properties HSGAN effectively deploys the compact latent topology information as a graph representation in the generative learning process and generates realistic point clouds, HSGAN avoids multiple discriminator updates per generator update, and HSGAN preserves the most dominant geometric structures of 3D shapes in the same hierarchical sampling process. We demonstrate the performance of our new approach with both quantitative and qualitative evaluations. We further present a new adversarial loss to maintain the training stability and overcome the potential mode collapse of traditional GANs. Finally, we explore the use of HSGAN as a plug-and-play decoder in the auto-encoding architecture.

Exploration of CT manifestations of different clinical types of novel coronavirus pneumonia.

BACKGROUND: To explore computed tomography (CT) characteristics of the 2019 novel coronavirus (COVID-19) pneumonia and explore variations among the different clinical types. METHODS: Clinical and CT imaging data of 43 patients diagnosed with COVID-19 in our hospital and the cooperative hospital between January 15-30, 2020 were collected (27 male and 16 female). Patients were classified as common type (26 cases, 60%), severe type (14 cases, 33%) or critical type (three cases, 7%) according to the new coronavirus pneumonia treatment scheme (sixth edition). Patient clinical data and CT images were analyzed and evaluated. RESULTS: Fever was the main symptom in common type COVID-19 cases (23/26, 88.46%). Both severe and critical type COVID-19 patients had fever and cough symptoms, and dyspnea was observed in all three critical COVID-19 patients. CT manifestations in the common type COVID-19 cohort were bilateral involvement (20/26, 71%), multiple lesions (14/26, 54%), ground-glass density shadow (17/26, 65%), and some cases were accompanied by local consolidation (9/26, 35%), which is consistent with early stage COVID-19 CT performance. CT manifestations in the severe and critical types involved both lungs. Severe COVID-19 cases predominantly consisted of multiple mixed-density lesions (10/14, 71%), and a few patients showed diffuse lung glass density shadows in both lungs (4/14, 29%), which is consistent with the progression stage COVID-19 CT performance. Critical COVID-19 cases exhibited mixed-density lesions, and two cases displayed "white lung", which is the CT manifestation at the severe COVID-19 stage. Only one critical COVID-19 patient had pleural effusion. CONCLUSIONS: The CT manifestations of COVID-19 are specific and there are variations between different clinical types. Thus, CT is an important clinical tool for early diagnosis and assessment of the severity of COVID-19.

Transient visual acuity loss after spine surgery in the prone position: a case report and literature review.

Visual loss after spine surgery in the prone position is a disastrous postoperative complication because it is almost irreversible. Additionally, the optimal treatments and recommended professional guidelines for visual loss after spine surgery are deficient. A 43-year-old man developed visual loss after spine surgery in the prone position. Immediate ophthalmic consultation confirmed central retinal artery occlusion. Therefore, combined therapies were administered, including neurotrophy, anticoagulation, vasodilation, and adequate fluid infusion, followed by hyperbaric oxygen treatment. After active treatment, his visual acuity gradually recovered from 5 hours postoperatively and continued to improve thereafter. We reviewed the literature on postoperative visual loss with a focus on spine surgery in the prone position. Because the etiology of this complication is complex and has few effective treatments, the best method for its avoidance is to pay close attention to preventing it during surgery.

Excellent low-temperature NH3-SCR NO removal performance and enhanced H2O resistance by Ce addition over the Cu0.02Fe0.2CeyTi1-yOx (y = 0.1, 0.2, 0.3) catalysts.

In the present work, a serial of Cu0.02Fe0.2CeyTi1-yOx catalysts are prepared by sol-gel method and applied for NH3-SCR of NO, meanwhile Cu0.02Fe0.2Ce0.2Ti0.8Ox shows good low-temperature NH3-SCR performance with/without water and an outstanding water resistance. The bulk structure, redox ability, surface acidity and surface species of Cu0.02Fe0.2CeyTi1-yOx are measured and discussed by series of characterization in details to illuminate the reasons for the good low-temperature activity and water resistance. The Ce modification can tune the surface acidic distribution, improve the surface oxygen content and surface oxidation reduction cycle (Ce4+ + Fe2+ ↔ Ce3+ + Fe3+), which contribute the good activity. In addition, the effect of water on NH3-SCR performance over Cu0.02Fe0.2TiOx and Cu0.02Fe0·2Ce0·2Ti0.8Ox are investigated emphatically by in situ DRIFTS.

Moxibustion alleviates intervertebral disc degeneration via activation of the HIF-1α/VEGF pathway in a rat model.

Intervertebral disc degeneration (IDD) induces serious back, neck and radicular pain. Recently, moxibustion has been suggested as an effective treatment for IDD. Thus, our study aims to investigate the molecular mechanism of moxibustion in IDD. A rat model of IDD was established by moxibustion treatment. Nucleus pulposus (NP) cells isolated from IDD rats or IDD rats treated with moxibustion were transfected with plasmids harboring overexpressed hypoxia-inducible factor-1 alpha (HIF-1α) to understand the role of treatment on cell autophagy and apoptosis. To investigate the mechanism of moxibustion in IDD, aggrecan, cyclo-oxygenase 2 (COX-2), HIF-1α and vascular endothelial growth factor (VEGF) expression in NP cells was measured. The expression of aggrecan and COX-2 was elevated by moxibustion treatment. Moxibustion induced autophagy and suppressed apoptosis of NP cells from IDD rats. Compared with IDD rats, the expression of light chain 3 (LC3) II/I, Beclin-1, B-cell lymphoma-2 (Bcl-2) and HIF-1α was regulated significantly after moxibustion treatment, while the expression of cleaved-caspase-3, Bcl-2 associated protein X and VEGF was downregulated. In general, moxibustion may be beneficial to IDD by enhancing autophagy and reducing apoptosis of NP cells via the HIF-1α/VEGF pathway.

ProLo: Localization via Projection for Three-Dimensional Mobile Underwater Sensor Networks.

We study the problem of three-dimensional localization of the underwater mobile sensor networks using only range measurements without GPS devices. This problem is challenging because sensor nodes often drift with unknown water currents. Consequently, the moving direction and speed of a sensor node cannot be predicted. Moreover, the motion devices of the sensor nodes are not accurate in underwater environments. Therefore, we propose an adaptive localization scheme, ProLo, taking these uncertainties into consideration. This scheme applies the rigidity theory and maintains a virtual rigid structure through projection. We have proved the correctness of this three-dimensional localization scheme and also validated it using simulation. The results demonstrate that ProLo is promising for real mobile underwater sensor networks with various noises and errors.

Trend in relative survival in squamous cervical cancer by decade from 1983 to 2012: a period analysis.

OBJECTIVE: Squamous cervical cancer (SCC), the predominant histological type, represents approximately 75-80% of all cervical cancers. Although the overall incidence of cervical cancer has declined worldwide, the data describing the changes in the incidence and long-term survival in SCC remain limited. METHODS: The data were extracted from Surveillance, Epidemiology, and End Results (SEER) registries for an evaluation of the changes in the incidence and survival associated with SCC during 1983-2012. In addition, the patients with SCC were stratified by age, race, and socioeconomic status (SES). Stata 12.0 software was used to perform the Cox regression and Spearman's rank correlation analyses. RESULTS: The overall incidence of SCC constantly declined from 7.3 to 5.6 to 4.3 per 100,000 people; the peak age of incidence was 55-69 years in the first decade, while the 40-54 age group served as another incidence peak in the last 2 decades. Median survival increased from 189 months to 231 months in the first 2 decades and was not reached in the third decade. The 10-year relative survival rates (RSRs) changed from 63.2% to 66.5% to 62.1% across the 3 decades. Additionally, the survival gaps narrowed from 13% to 8% between Whites and Blacks and from 5.4% to 3.5% between low- and medium-poverty groups in the 3 decades. CONCLUSION: This study demonstrated a declining incidence over the 3 decades with an improvement in median survival. However, the relative survival associated with SCC did not improve in the last decade. Furthermore, the survival gaps between races and various SESs significantly narrowed over the 3 decades.

Comparison of two training methods in community pharmacy: Project VACCINATE.

OBJECTIVE: To compare the impact of a whole-staff training strategy with a train-the-trainer strategy on 1) the number of influenza, pneumococcal, herpes zoster, and pertussis vaccines administered by community pharmacists to adults; 2) staff confidence; and 3) fidelity to the intervention. SETTING: Eight Quality Food Centers (QFC) Pharmacies in Seattle, Washington. PRACTICE DESCRIPTION: QFC Pharmacy is a grocery store division of The Kroger Co. with 30 pharmacies located in Washington State. QFC provides all routine and travel vaccines to adolescents and adults and has a culture of improving vaccine access to its community. PRACTICE INNOVATION: Pharmacists and pharmacy technicians from 8 QFC pharmacies received training to enhance their immunization care for adults. The entire staff from 4 pharmacies received whole-staff training, and staff members from the other 4 pharmacies received a train-the-trainer approach. The whole-staff training group had all staff members attend a live, 2-hour training. The train-the-trainer group sent 1 pharmacist and 1 pharmacy technician champion to attend the live training and then return to their pharmacy to train the other staff members. EVALUATION: The number of immunizations administered, staff confidence, and self-reported fidelity to the intervention were measured before and after training. All data were analyzed using descriptive statistics. RESULTS: The number of total influenza, pneumococcal, herpes zoster, and pertussis vaccines administered increased 12.6% in the whole-staff training group and 15.2% in the train-the-trainer group. Both training strategies increased confidence in identifying patients eligible for vaccines, talking to patients about vaccine needs, and using the bidirectional immunization platform. Pharmacy staff members in both groups indicated fidelity to key steps in the intervention process. CONCLUSION: Both whole-staff training and train-the-trainer approaches were associated with an improvement in the number of vaccines administered, staff confidence, and fidelity to the intervention. Community pharmacy organizations could use either training strategy when implementing enhancements to an existing patient care service. The train-the-trainer strategy may be less resource intensive.

Long-Term Survival Rates of Patients with Stage III-IV Hodgkin Lymphoma According to Age, Sex, Race, and Socioeconomic Status, 1984-2013.

BACKGROUND: Long-term survival rates for patients with stage III-IV Hodgkin lymphoma, or advanced Hodgkin lymphoma (aHL), have increased substantially since the 1960s. Because large-scale research of aHL is rare, we aimed to demonstrate the differences in incidence and survival of aHL according to four patient variables in recent decades, with a focus on the outcomes of treatment of aHL and the advancement of public health care. MATERIALS AND METHODS: Data on aHL cases diagnosed during 1984-2013 were extracted from the Surveillance, Epidemiology, and End Results Program database. Relative survival, Kaplan-Meier, and Cox proportional hazards regression analyses were performed to identify prognosis indicators for aHL. RESULTS: The incidence rates for aHL were 1.1, 0.8, and 1.0 per 100,000 in the first, second, and third decades, respectively, during 1984-2013. The 120-month relative survival rate improved continuously in each decade from 58.5% to 64.6% to 72.1%. In addition, disparities in the 120-month relative survival rate between male and female patients and among patients of different races narrowed over time. The difference in long-term survival rate between the poor (medium and high poverty) and rich (low poverty) groups narrowed across the 3 decades. CONCLUSION: The long-term survival rate for patients with aHL increased in each decade, whereas survival rate disparities according to sex, race, and socioeconomic status narrowed, except for older patients aged >60 years and the high-poverty group. IMPLICATIONS FOR PRACTICE: Long-term survival rates of patients with advanced Hodgkin lymphoma were elaborated in this article. The disparities according to sex, race, and socioeconomic status of survival condition were analyzed and showed the development of the public health care system and modern medicine technology.