Risk factors associated with ototoxicity in long-term nasopharyngeal carcinoma survivors.

PURPOSE: To investigate patient-reported outcomes among long-term survivors and to analyze their associated risk factors to provide better treatment and symptom management for nasopharyngeal carcinoma patients. MATERIALS AND METHODS: This retrospective study collected patients diagnosed with nasopharyngeal carcinoma who received radical intensity-modulated radiotherapy in our hospital from June 2009 to June 2016. The patients' disease status and patient-reported outcomes were analyzed by follow-up. The ototoxicity was graded according to CTCAE 5.0. RESULTS: A total of 223 patients were included in the study. Among the enrolled patients, the median follow-up time was 8.4 (6.0-13.0) years. Based on the patient-reported outcomes, ototoxicity was the most common symptom (52.9 %). After univariable and multivariable logistic regression, age ≥ 50 years old (OR, 4.066; 95 % CI, 1.799-9.190; P = .001), diabetes (OR, 3.520; 95 % CI, 1.442-8.591; P = .006), D2 ≥ 69 Gy (OR, 3.715; 95 % CI, 1.064-12.969; P = . 040) and V35 ≥ 91.5 % (OR, 3.398; 95 % CI, 1.113-10.372; P = .032) were associated with a higher incidence of grade 3-4 ototoxicity. Then, we constructed the individual nomogram and the C index of the graph was 0.815. By univariable logistic regression, we found that grade 3-4 ototoxicity was associated with an increased risk of multiple other symptoms, dysmasesia, tongue dysfunction, hoarseness, dysphagia and ocular toxicity. CONCLUSION: In long-term survivors of nasopharyngeal carcinoma patients receiving IMRT, the most common patient-reported outcome was ototoxicity. Age ≥ 50 years, diabetes, ear exposure dose of D2 ≥ 69 Gy and V35 ≥ 91.5 % are independent risk factors for grade 3-4 ototoxicity.

The diversity of inhibitory receptor co-expression patterns of exhausted CD8+ T cells in oropharyngeal carcinoma.

Exhausted CD8+ T cells (Texs) are characterized by the expression of various inhibitory receptors (IRs), whereas the functional attributes of these co-expressed IRs remain limited. Here, we systematically characterized the diversity of IR co-expression patterns in Texs from both human oropharyngeal squamous cell carcinoma (OPSCC) tissues and syngeneic OPSCC model. Nearly 60% of the Texs population co-expressed two or more IRs, and the number of co-expressed IRs was positively associated with superior exhaustion and cytotoxicity phenotypes. In OPSCC patients, programmed cell death-1 (PD-1) blockade significantly enhanced PDCD1-based co-expression with other IR genes, whereas dual blockades of PD-1 and cytotoxic T lymphocyte-associated protein 4 (CTLA-4) significantly upregulated CTLA4-based co-expression with other IR genes. Collectively, our findings demonstrate that highly diverse IR co-expression is a leading feature of Texs and represents their functional states, which might provide essential clues for the rational selection of immune checkpoint inhibitors in treating OPSCC.

Improved antitumor effects elicited by an oncolytic HSV-1 expressing a novel B7H3nb/CD3 BsAb.

Oncolytic viruses have emerged as a promising modality for cancer treatment due to their unique abilities to directly destroy tumor cells and modulate the tumor microenvironment. Bispecific T-cell engagers (BsAbs) have been developed to activate and redirect cytotoxic T lymphocytes, enhancing the antitumor response. To take advantage of the specific infection capacity and carrying ability of exogenous genes, we generated a recombinant herpes simplex virus type 1 (HSV-1), HSV-1dko-B7H3nb/CD3 or HSV-1dko-B7H3nb/mCD3, carrying a B7H3nb/CD3 or B7H3nb/mCD3 BsAb that replicates and expresses BsAb in tumor cells in vitro and in vivo. The new generation of oncolytic viruses has been genetically modified using CRISPR/Cas9 technology and the cre-loxp system to increase the efficiency of HSV genome editing. Additionally, we used two fully immunocompetent models (GL261 and MC38) to assess the antitumor effect of HSV-1dko-B7H3nb/mCD3. Compared with the HSV-1dko control virus, HSV-1dko-B7H3nb/mCD3 induced enhanced anti-tumor immune responses and T-cell infiltration in both GL261 and MC38 models, resulting in improved treatment efficacy in the latter. Furthermore, flow cytometry analysis of the tumor microenvironment confirmed an increase in NK cells and effector CD8+ T cells, and a decrease in immunosuppressive cells, including FOXP3+ regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and CD206+ macrophages (M2). Overall, our study identified a novel camel B7H3 nanobody and described the genetic modification of the HSV-1 genome using CRISPR/Cas9 technology and the cre-loxp system. Our findings indicate that expressing B7H3nb/CD3 BsAb could improve the antitumor effects of HSV-1 based oncolytic virus.

Tyrosine kinase inhibitors for radioiodine refractory differentiated thyroid cancer: A systematic review and meta-analysis.

BACKGROUND: The poor overall prognosis of radioiodine refractory thyroid cancer is an inevitable challenge in managing this disease. A series of trials have demonstrated the antitumor activity of tyrosine kinase inhibitors (TKIs) in radioiodine refractory differentiated thyroid cancer (RAIR-DTC). However, the available evidence cannot determine the optimal choice of TKI in RAIR-DTC. METHODS: This study searched PubMed, EMBASE, Cochrane databases, and the ClinicalTrials website. The Cochrane bias risk tool was used to assess the risk of bias, and to evaluate randomized clinical trials (RCT) of RAIR-DTC patients treated with the TKI system. Outcomes, including progression-free survival (PFS), overall survival (OS), and adverse events (AEs) were reported. RESULTS: Seven studies involving 1310 patients with RAIR-DTC was conducted to compare the PFS and OS of various TKI monotherapies with placebo. The results showed that all TKI monotherapies had a statistically significant benefit in terms of PFS compared with placebo, with lenvatinib demonstrating the greatest benefit (hazard ratio [HR] 0.19, 95% credible interval [CrI] 0.14-0.25). In terms of OS, only apatinib (HR 0.42, 95% CrI 0.18-0.97) and anlotinib (HR 0.36, 95% CrI 0.18-0.73) showed statistically significant benefits compared with placebo. TKIs also had a higher incidence of AEs of grade 3 or higher compared with placebo. The findings suggest that lenvatinib may be the preferred TKI for the treatment of RAIR-DTC, although its high incidence of AEs should be considered. The results also indicate that TKI treatment may be similarly effective in RAIR-DTC patients with BRAF or RAS mutations and in those with papillary or follicular subtypes of the disease, regardless of prior TKI treatment. CONCLUSIONS: The results of this meta-analysis suggest that targeted therapy with TKIs may be beneficial for patients with radioiodine-refractory advanced or metastatic differentiated thyroid cancer. Among the TKIs analyzed, lenvatinib appeared to be the most effective at improving PFS, although it also had the highest incidence of AEs. Further research through direct randomized controlled trials is needed to determine the optimal choice of TKI for treating patients with RAIR-DTC. This study is beneficial for formulating patients' treatment plans and guides clinicians' decision-making.

Acute Large Dose Irradiation Sensitizes Surviving Cells to Subsequent Irradiation; Implications for Stereotactic Body Radiation Therapy.

To determine if the radiation sensitivity of cells that survive acute high-dose radiation exposure used in stereotactic body radiation therapy (SBRT), differs from the sensitivity of non-irradiated cells and cells that survive multiple 2 Gy doses of radiation. Isogenic rodent and two human tumor cell lines were exposed to 14 × 2 Gy of radiation, or a single acute dose of 12 Gy. The most resistant cell line was also exposed to an acute dose of 15 Gy. One week after 12 Gy, and 4 days after 14 × 2 Gy, surviving cells were exposed to 0-8 Gy in 2 Gy doses and cell survival was assessed by colony formation. In addition, the colony forming efficiency of 12 Gy survivors was evaluated for 1 month postirradiation. For cells exposed to 15 Gy, the response of surviving cells to 6 Gy was determined for up to 35 days postirradiation and compared to the 6 Gy surviving fraction of control cells. The radiation sensitivity of cells that survived 12 Gy exposure, and cells that survived 14 fractions of 2 Gy irradiation did not differ from the response of unirradiated control cells. However, the growth rate and colony forming efficiency of 12 Gy survivors was transiently reduced for greater than 2 weeks postirradiation. In contrast to the unchanged sensitivity of 12 Gy surviving cells at day 7 postirradiation, 15 Gy survivors exhibited enhanced sensitivity to radiation for up to 21 days postirradiation and suggests a biological basis for SBRT.

Streptococcus salivarius K12 Alleviates Oral Mucositis in Patients Undergoing Radiotherapy for Malignant Head and Neck Tumors: A Randomized Controlled Trial.

PURPOSE: Oral mucositis (OM) is a common debilitating toxicity associated with radiotherapy (RT) for malignant head and neck tumors. This prospective, randomized, double-blind, placebo-controlled trial aimed to evaluate the efficacy and safety of Streptococcus salivarius K12 (SsK12) in reducing the incidence, duration, and severity of severe OM (SOM). METHODS: A total of 160 patients with malignant head and neck tumors undergoing definitive or postoperative adjuvant RT were randomly assigned (1:1) to receive SsK12 probiotic (n = 80) or placebo (n = 80) at West China Hospital, Sichuan University, Chengdu, China. Patients were instructed to suck SsK12 or placebo lozenges thrice daily from the initiation to the end of RT. OM was evaluated twice a week during RT and once a week thereafter for up to 8 weeks. The primary end point was the incidence of SOM. Adverse events were assessed according to the National Cancer Institute Common Terminology Criteria for Adverse Events, version 5.0. RESULTS: Baseline patient characteristics were similar in the SsK12 and placebo groups. The incidence of SOM was significantly lower in the SsK12 group as compared with the placebo group (36.6% v 54.2%; P = .0351). The duration (median, 0.0 days v 7.0 days; mean, 8.9 days v 18.3 days; P = .0084) and time to develop SOM (median, not estimable v 42.0 days; hazard ratio, 0.55 [95% CI, 0.34 to 0.89]; log-rank test: P = .0123) were also improved in the case of the SsK12 group. Adverse events were similar between the groups, and mild or moderate gastrointestinal reactions (flatulence or dyspepsia) associated with the lozenges were observed in two patients in the SsK12 group. High-throughput sequencing results indicated that SsK12 inhibited opportunistic pathogens and enriched oral commensals during RT. CONCLUSION: In this prospective, randomized clinical trial, SsK12 probiotic significantly reduced the incidence, onset, and duration of SOM with a good safety profile.

The association between aspirin use and immune-related adverse events in specific cancer patients receiving ICIs therapy: analysis of the FAERS database.

Background: The promise of immune checkpoint inhibitors (ICIs) therapy in cancer treatment is tempered by the occurrence of immune-related adverse events (irAEs). Many patients undergoing ICIs also take aspirin, but the association between aspirin and irAEs is not well understood. Methods: This study analyzed adverse reaction data associated with the use of ICIs in the US Food and Drug Administration (FDA) Adverse Event Reporting System FDA Adverse Event Reporting System database, from the approval date of each drug until 1 October 2022. Multivariate logistic regression was employed to assess the association of aspirin use with irAEs in patients receiving ICIs. Results: The results indicated that aspirin use was associated with an increased risk of irAEs in a pan-cancer analysis, with a more pronounced association in specific cancer types such as lung cancer, mesothelioma, and pancreatic cancer. However, in lymphoma, aspirin use was associated with a reduced risk of irAEs. Furthermore, aspirin use was associated with an increased risk of certain irAEs, such as anemia, colitis, myocarditis, myositis, pancreatitis, pericarditis, and pneumonia, while it was associated with a reduced risk of rash, Stevens-Johnson syndrome, and thyroiditis. Conclusion: This study has unveiled an association between aspirin use and irAEs in cancer patients receiving ICIs therapy, emphasizing the need for individualized consideration of patients' medication history when devising cancer treatment plans to enhance efficacy and reduce risks.

Advances and challenges of immunotherapies in NK/T cell lymphomas.

Natural killer (NK)/T cell lymphoma (NKTCL) is a rare subtype of Epstein-Barr virus (EBV)-associated non-Hodgkin lymphoma characterized by poor clinical outcomes. It is more common in East Asian and Latin American countries. Despite the introduction of asparaginase/pegaspargase-based chemotherapy, the prognosis of patients with advanced NKTCL needs to be improved, and few salvage treatment options are available for relapsed/refractory patients who fail chemotherapy. Although many unknowns remain, novel treatment strategies to further improve outcomes are urgently needed. Immunotherapy has emerged and shown favorable antitumor activity in NKTCL, including monoclonal antibodies targeting immune checkpoint inhibitors, other receptors on the cellular membrane, and cellular immunotherapy, which could enhance immune cells attack on tumor cells. In this review, we provide an overview of recent immunotherapy in NKTCL, focusing on programmed cell death-1 (PD-1)/programmed cell death-ligand 1 (PD-L1), cytotoxic T lymphocyte-associated protein 4 (CTLA-4), chimeric antigen receptor (CAR) T cells, EBV-specific cytotoxic T lymphocytes, immunomodulatory agents, and other targeted agents, as well as the current progress and challenges in the field.

Association between BMI trajectories in late-middle age and subsequent dementia risk in older age: a 26-year population-based cohort study.

BACKGROUND: The association between body mass index (BMI) and dementia risk differs depending on follow-up time and age at BMI measurement. The relationship between BMI trajectories in late-middle age (50-65 years old) and the risk of dementia in older age (> 65 years old) has not been revealed. METHODS: In the present study, participants from the Health and Retirement Study were included. BMI trajectories were constructed by combining BMI trend and variation information. The association between BMI trajectories at the age of 50-65 years and dementia risk after the age of 65 years was investigated. Participants with European ancestry and information on polygenic scores for cognitive performance were pooled to examine whether genetic predisposition could modify the association. RESULTS: A total of 10,847 participants were included in the main analyses. A declining BMI trend and high variation in late-middle age were associated with the highest subsequent dementia risk in older age compared with an ascending BMI trend and low variation (RR = 1.76, 95% CI = 1.45-2.13). Specifically, in stratified analyses on BMI trajectories and dementia risk based on each individual's mean BMI, the strongest association between a declining BMI trend with high variation and elevated dementia risk was observed in normal BMI group (RR = 2.66, 95% CI = 1.72-4.1). Similar associations were found when participants were stratified by their genetic performance for cognition function without interaction. CONCLUSIONS: A declining BMI trend and high variation in late-middle age were associated with a higher risk of dementia. Early monitoring of these individuals is needed to prevent dementia in older individuals.

Automated treatment planning for liver cancer stereotactic body radiotherapy

Purpose To evaluate the quality of fully automated stereotactic body radiation therapy (SBRT) planning based on volumetric modulated arc therapy, which can reduce the reliance on historical plans and the experience of dosimetrists. Methods Fully automated re-planning was performed on twenty liver cancer patients, automated plans based on automated SBRT planning (ASP) program and manual plans were conducted and compared. One patient was randomly selected and evaluate the repeatability of ASP, ten automated and ten manual SBRT plans were generated based on the same initial optimization objectives. Then, ten SBRT plans were generated for another selected randomly patient with different initial optimization objectives to assess the reproducibility. All plans were clinically evaluated in a double-blinded manner by five experienced radiation oncologists. Results Fully automated plans provided similar planning target volume dose coverage and statistically better organ at risk sparing compared to the manual plans. Notably, automated plans achieved significant dose reduction in spinal cord, stomach, kidney, duodenum, and colon, with a median dose of D2% reduction ranging from 0.64 to 2.85 Gy. R50% and Dmean of ten rings for automated plans were significantly lower than those of manual plans. The average planning time for automated and manual plans was 59.8 ± 7.9 min vs. 127.1 ± 16.8 min (− 67.3 min). Conclusion Automated planning for SBRT, without relying on historical data, can generate comparable or even better plan quality for liver cancer compared with manual planning, along with better reproducibility, and less clinically planning time (AU)

Glycolysis-cholesterol metabolic axis in immuno-oncology microenvironment: emerging role in immune cells and immunosuppressive signaling.

Cell proliferation and function require nutrients, energy, and biosynthesis activity to duplicate repertoires for each daughter. It is therefore not surprising that tumor microenvironment (TME) metabolic reprogramming primarily orchestrates the interaction between tumor and immune cells. Tumor metabolic reprogramming affords bioenergetic, signaling intermediates, and biosynthesis requirements for both malignant and immune cells. Different immune cell subsets are recruited into the TME, and these manifestations have distinct effects on tumor progression and therapeutic outcomes, especially the mutual contribution of glycolysis and cholesterol metabolism. In particularly, glycolysis-cholesterol metabolic axis interconnection plays a critical role in the TME modulation, and their changes in tumor metabolism appear to be a double-edged sword in regulating various immune cell responses and immunotherapy efficacy. Hence, we discussed the signature manifestation of the glycolysis-cholesterol metabolic axis and its pivotal role in tumor immune regulation. We also highlight how hypothetical combinations of immunotherapy and glycolysis/cholesterol-related metabolic interventions unleash the potential of anti-tumor immunotherapies, as well as developing more effective personalized treatment strategies.

mRNA-LNP vaccination-based immunotherapy augments CD8+ T cell responses against HPV-positive oropharyngeal cancer.

Although mRNA vaccines are known as potent activators of antigen-specific immune responses against infectious diseases, limited understanding of how they drive the functional commitment of CD8+ T cells in tumor microenvironment (TME) and secondary lymphoid organs hinders their broader application in cancer immunotherapy. Here, we systematically evaluated the immunological effects of a lipid nanoparticle (LNP)-encapsulated mRNA vaccine that encodes human papillomavirus E7 protein (HPV mRNA-LNP), a tumor-specific antigen of HPV-positive oropharyngeal squamous cell carcinoma (OPSCC). HPV mRNA-LNP vaccination activated overall and HPV-specific CD8+ T cells, as well as differentially drove the functional commitment of CD8+ T cells through distinct IFN-response and exhaustion trajectories in the spleen and TME, respectively. Combination therapies of HPV mRNA-LNP vaccination with immune checkpoint blockades boosted HPV-specific CD8+ T cells while maintaining their anti-tumor function, thus further promoting tumor regression. Our results showed that the HPV mRNA-LNP vaccination combined with immune checkpoint blockade is a promising approach for immunotherapy of HPV-positive OPSCC.

Evaluating the Causal Association between Inflammatory Bowel Disease and Risk of Atherosclerotic Cardiovascular Disease: Univariable and Multivariable Mendelian Randomization Study.

BACKGROUND: Observational studies suggested that inflammatory bowel disease (IBD) (i.e., Crohn's disease [CD] and ulcerative colitis [UC]) is associated with an increased risk of atherosclerotic cardiovascular disease (ASCVD), including coronary artery disease (CAD) and ischemic stroke. However, it is still unclear whether the observed associations causally exist. Thus, we aim to examine the potential effect of IBD, CD, and UC on the risk of CAD and ischemic stroke, using a two-sample Mendelian randomization (MR) study. METHODS: Genetic instruments for IBD, CD, and UC were retrieved from the latest published genome-wide association studies (GWASs) of European ancestry. GWAS summary data for instrument-outcome associations were gathered from four independent resources: CARDIoGRAMplusC4D Consortium, MEGASTROKE consortium, FinnGen, and UK Biobank. The inverse variance weighted (IVW) method and multiple pleiotropy-robust approaches were conducted and, subsequently, combined in a fixed-effect meta-analysis. Moreover, multivariable MR (MVMR) analysis was conducted to adjust for potential influencing instrumental variables. RESULTS: The IVW method revealed no causal effect of IBD on the risk of CAD (overall IBD on CAD: OR 1.003, 95%CI 0.982 to 1.025; CD on CAD: OR 0.997, 95%CI 0.978 to 1.016; UC on CAD: OR 0.986, 95%CI 0.963 to 1.010) or the risk of ischemic stroke (overall IBD on ischemic stroke: OR 0.994, 95%CI 0.970 to 1.018; CD on ischemic stroke: OR 0.996, 95%CI 0.979 to 1.014; UC on ischemic stroke: OR 0.999, 95%CI 0.978 to 1.020). The results of the meta-analysis and MVMR remained consistent. CONCLUSION: Our MR analysis does not support a causal effect of IBD on CAD and ischemic stroke, and previous results from observational studies might be biased through uncontrolled confoundings (such as IBD-specific medications and detection bias, etc.) that warrant further research.

Association between inflammatory bowel disease and pancreatic cancer: results from the two-sample Mendelian randomization study.

Background: The nuanced relationship between inflammatory bowel disease (IBD) and pancreatic cancer is noticed in recent years. However, the underlying causal effects of these two diseases are still unclear. Methods: The two-sample mendelian randomization (MR) was conducted to explore the causal effect of IBD condition on pancreatic cancer. Methods of Wald ratio, inverse variance weighted (IVW), MR-Egger, weighted median, and weighted mode were used to investigate the causal relationship between IBD and pancreatic cancer. Besides, Cochrane's Q test, MR-Egger, and leave-one-out method were further conducted to detect heterogeneity, stability, and pleiotropy of MR results. Results: In the MR analysis, we found Crohn's disease had a significant causal effect on pancreatic cancer. Specifically, Crohn's disease would increase 11.1% the risk of pancreatic cancer by the IVW method (p= 0.022), 33.8% by MR Egger (p= 0.015), by 35.3% by the Weighted model (p= 0.005). Regarding ulcerative colitis, there was no statistically significant causal effect observed on pancreatic cancer (p>0.05). Additionally, the pleiotropic test and Leave-one-out analysis both proved the validity and reliability of the present two-sample MR analyses. Conclusion: This study indicates that IBD, particularly Crohn's disease, is causality associated with increased risk of pancreatic cancer. Our results may help public health managers to make better follow-up surveillance of IBD patients.

Unsupervised Domain Adaptive Dose Prediction via Cross-Attention Transformer and Target-Specific Knowledge Preservation.

Radiotherapy is one of the leading treatments for cancer. To accelerate the implementation of radiotherapy in clinic, various deep learning-based methods have been developed for automatic dose prediction. However, the effectiveness of these methods heavily relies on the availability of a substantial amount of data with labels, i.e. the dose distribution maps, which cost dosimetrists considerable time and effort to acquire. For cancers of low-incidence, such as cervical cancer, it is often a luxury to collect an adequate amount of labeled data to train a well-performing deep learning (DL) model. To mitigate this problem, in this paper, we resort to the unsupervised domain adaptation (UDA) strategy to achieve accurate dose prediction for cervical cancer (target domain) by leveraging the well-labeled high-incidence rectal cancer (source domain). Specifically, we introduce the cross-attention mechanism to learn the domain-invariant features and develop a cross-attention transformer-based encoder to align the two different cancer domains. Meanwhile, to preserve the target-specific knowledge, we employ multiple domain classifiers to enforce the network to extract more discriminative target features. In addition, we employ two independent convolutional neural network (CNN) decoders to compensate for the lack of spatial inductive bias in the pure transformer and generate accurate dose maps for both domains. Furthermore, to enhance the performance, two additional losses, i.e. a knowledge distillation loss (KDL) and a domain classification loss (DCL), are incorporated to transfer the domain-invariant features while preserving domain-specific information. Experimental results on a rectal cancer dataset and a cervical cancer dataset have demonstrated that our method achieves the best quantitative results with [Formula: see text], [Formula: see text], and HI of 1.446, 1.231, and 0.082, respectively, and outperforms other methods in terms of qualitative assessment.

Liquid‒liquid phase separation: roles and implications in future cancer treatment.

Liquid‒liquid phase separation (LLPS) is a phenomenon driven by weak interactions between biomolecules, such as proteins and nucleic acids, that leads to the formation of distinct liquid-like condensates. Through LLPS, membraneless condensates are formed, selectively concentrating specific proteins while excluding other molecules to maintain normal cellular functions. Emerging evidence shows that cancer-related mutations cause aberrant condensate assembly, resulting in disrupted signal transduction, impaired DNA repair, and abnormal chromatin organization and eventually contributing to tumorigenesis. The objective of this review is to summarize recent advancements in understanding the potential implications of LLPS in the contexts of cancer progression and therapeutic interventions. By interfering with LLPS, it may be possible to restore normal cellular processes and inhibit tumor progression. The underlying mechanisms and potential drug targets associated with LLPS in cancer are discussed, shedding light on promising opportunities for novel therapeutic interventions.

A Random Forest Model for Post-Treatment Survival Prediction in Patients with Non-Squamous Cell Carcinoma of the Head and Neck.

BACKGROUND: Compared to squamous cell carcinoma, head and neck non-squamous cell carcinoma (HNnSCC) is rarer. Integrated survival prediction tools are lacking. METHODS: 4458 patients of HNnSCC were collected from the SEER database. The endpoints were overall survivals (OSs) and disease-specific survivals (DSSs) of 3 and 5 years. Cases were stratified-randomly divided into the train & validation (70%) and test cohorts (30%). Tenfold cross validation was used in establishment of the model. The performance was evaluated with the test cohort by the receiver operating characteristic, calibration, and decision curves. RESULTS: The prognostic factors found with multivariate analyses were used to establish the prediction model. The area under the curve (AUC) is 0.866 (95%CI: 0.844-0.888) for 3-year OS, 0.862 (95%CI: 0.842-0.882) for 5-year OS, 0.902 (95%CI: 0.888-0.916) for 3-year DSS, and 0.903 (95%CI: 0.881-0.925) for 5-year DSS. The net benefit of this model is greater than that of the traditional prediction methods. Among predictors, pathology, involved cervical nodes level, and tumor size are found contributing the most variance to the prediction. The model was then deployed online for easy use. CONCLUSIONS: The present study incorporated the clinical, pathological, and therapeutic features comprehensively and established a clinically effective survival prediction model for post-treatment HNnSCC patients.

A Transformer-Embedded Multi-Task Model for Dose Distribution Prediction.

Radiation therapy is a fundamental cancer treatment in the clinic. However, to satisfy the clinical requirements, radiologists have to iteratively adjust the radiotherapy plan based on experience, causing it extremely subjective and time-consuming to obtain a clinically acceptable plan. To this end, we introduce a transformer-embedded multi-task dose prediction (TransMTDP) network to automatically predict the dose distribution in radiotherapy. Specifically, to achieve more stable and accurate dose predictions, three highly correlated tasks are included in our TransMTDP network, i.e. a main dose prediction task to provide each pixel with a fine-grained dose value, an auxiliary isodose lines prediction task to produce coarse-grained dose ranges, and an auxiliary gradient prediction task to learn subtle gradient information such as radiation patterns and edges in the dose maps. The three correlated tasks are integrated through a shared encoder, following the multi-task learning strategy. To strengthen the connection of the output layers for different tasks, we further use two additional constraints, i.e. isodose consistency loss and gradient consistency loss, to reinforce the match between the dose distribution features generated by the auxiliary tasks and the main task. Additionally, considering many organs in the human body are symmetrical and the dose maps present abundant global features, we embed the transformer into our framework to capture the long-range dependencies of the dose maps. Evaluated on an in-house rectum cancer dataset and a public head and neck cancer dataset, our method gains superior performance compared with the state-of-the-art ones. Code is available at https://github.com/luuuwen/TransMTDP.

TransDose: Transformer-based radiotherapy dose prediction from CT images guided by super-pixel-level GCN classification.

Radiotherapy is a mainstay treatment for cancer in clinic. An excellent radiotherapy treatment plan is always based on a high-quality dose distribution map which is produced by repeated manual trial-and-errors of experienced experts. To accelerate the radiotherapy planning process, many automatic dose distribution prediction methods have been proposed recently and achieved considerable fruits. Nevertheless, these methods require certain auxiliary inputs besides CT images, such as segmentation masks of the tumor and organs at risk (OARs), which limits their prediction efficiency and application potential. To address this issue, we design a novel approach named as TransDose for dose distribution prediction that treats CT images as the unique input in this paper. Specifically, instead of inputting the segmentation masks to provide the prior anatomical information, we utilize a super-pixel-based graph convolutional network (GCN) to extract category-specific features, thereby compensating the network for the necessary anatomical knowledge. Besides, considering the strong continuous dependency between adjacent CT slices as well as adjacent dose maps, we embed the Transformer into the backbone, and make use of its superior ability of long-range sequence modeling to endow input features with inter-slice continuity message. To our knowledge, this is the first network that specially designed for the task of dose prediction from only CT images without ignoring necessary anatomical structure. Finally, we evaluate our model on two real datasets, and extensive experiments demonstrate the generalizability and advantages of our method.

Frailty trajectory predicts subsequent cognitive decline: A 26-year population-based longitudinal cohort study.

Frailty refers to a decline in the physiological functioning of one or more organ systems. It remained unclear whether variations in the trajectory of frailty over time were associated with subsequent cognitive change. The aim of the current study was to investigate the association between frailty trajectories and subsequent cognitive decline based on the Health and Retirement Study (HRS). A total of 15,454 participants were included. The frailty trajectory was assessed using the Paulson-Lichtenberg Frailty Index, while the cognitive function was evaluated using the Langa-Weir Classification. Results showed that severe frailty was significantly associated with the subsequent decline in cognitive function (ß [95% CI] = -0.21 [-0.40, -0.03], p = 0.03). In the five identified frailty trajectories, participants with mild frailty (inverted U-shaped, ß [95% CI] = -0.22 [-0.43, -0.02], p = 0.04), mild frailty (U-shaped, ß [95% CI] = -0.22 [-0.39, -0.06], p = 0.01), and frailty (ß [95% CI] = -0.34 [-0.62, -0.07], p = 0.01) were all significantly associated with the subsequent cognition decline in the elderly. The current study suggested that monitoring and addressing frailty trajectories in older adults may be a critical approach in preventing or mitigating cognitive decline, which had significant implications for healthcare.