A Prognostic Model Based on Nutritional Indexes for Patients With Pan-Cancer: A Real-World Cohort Study.

BACKGROUND: The aim was to identify the nutritional indexes, construct a prognostic model, and develop a nomogram for predicting individual survival probability in pan-cancers. METHODS: Nutritional indicators, clinicopathological characteristics, and previous major treatment details of the patients were collected. The enrolled patients were randomly divided into training and validation cohorts. Least absolute shrinkage and selection operator (Lasso) regression cross-validation was used to determine the variables to include in the cox regression model. The training cohort was used to build the prediction model, and the validation cohort was used to further verify the discrimination, calibration, and clinical effectiveness of the model. RESULTS: A total of 2020 patients were included. The median OS was 56.50 months (95% CI, 50.36-62.65 months). In the training cohort of 1425 patients, through Lasso regression cross-validation, 13 characteristics were included in the model. Cox proportional hazards model was developed and visualized as a nomogram. The C-indexes of the model for predicting 1-, 3-, 5-, and 10-year OS were 0.848, 0.826, 0.814, and 0.799 in the training cohort and 0.851, 0.819, 0.814, and 0.801 in the validation cohort. The model showed great calibration in the two cohorts. Patients with a score of less than 274.29 had a better prognosis (training cohort: HR, 6.932; 95% CI, 5.723-8.397; log-rank p < 0.001; validation cohort: HR, 8.429; 95% CI, 6.180-11.497; log-rank p < 0.001). CONCLUSION: The prognostic model based on the nutritional indexes of pan-cancer can divide patients into different survival risk groups and performed well in the validation cohort.

Can Virtual Reality-Assisted Therapy Offer Additional Benefits to Patients With Vestibular Disorders Compared With Conventional Vestibular Physical Therapy? A Meta-analysis.

OBJECTIVE: To determine whether virtual reality-assisted therapy (VRAT) significantly improves the treatment of peripheral or central vestibular disorders when compared with conventional vestibular physical therapy (CVPT) alone. Indicators of vestibular symptoms are used to determine this. DATA SOURCES: Two reviewers independently searched PubMed, EMBASE, ClinicalTrials.gov, Web of Science, and the Cochrane Collaboration database from January 2010 to January 2022 for studies reporting on VRAT in vestibular disorders. STUDY SELECTION: Randomized controlled trials (RCTs) were included that mainly focused on the following measures: the Dizziness Handicap Inventory (DHI), Simulator Sickness Questionnaire, visual analog scale, and balance measures such as the Activities-specific Balance Confidence Scale (ABC), timed Up and Go test, sensory organization test, and center of pressure. The primary outcome was assessment of symptomatic changes before and after VRAT. DATA EXTRACTION: Two authors independently conducted the literature search and selection. After screening, meta-analysis was performed on the RCTs using RevMan 5.3 software. DATA SYNTHESIS: The results showed that VRAT produced significantly greater improvement than CVPT alone in scores of DHI-Total (standardized mean difference [SMD]: -7.09, 95% confidence interval [CI]: [-12.17, -2.00], P=.006), DHI-Functional (SMD=-3.66, 95% CI: [-6.34, -0.98], P=.007), DHI-Physical (SMD=-3.14, 95% CI: [-5.46, -0.83], P=.008), and DHI-Emotional (SMD=-3.10, 95% CI: [-5.13, -1.08], P=.003). ABC scores did not show improvement (SMD: 0.58, 95% CI: [-3.69, 4.85], P=.79). Subgroup analysis showed that DHI-Total between-group differences were insignificant for central vestibular disorders (SMD=-1.47, 95% CI: [-8.71, -5.78], P=.69), although peripheral disorders showed significant improvements (SMD=-9.58, 95% CI: [-13.92, -5.25], P<.0001). However, the included studies showed high heterogeneity (I2>75%). CONCLUSIONS: VRAT may offer additional benefits for rehabilitation from vestibular diseases, especially peripheral disorders, when compared with CVPT alone. However, because of high heterogeneity and limited data, additional studies with a larger sample size and more sensitive and specific measurements are required to conclusively determine the evidence-based utility of virtual reality.

Development of a novel nomogram for predicting clinically significant prostate cancer with the prostate health index and multiparametric MRI.

Introduction: On prostate biopsy, multiparametric magnetic resonance imaging (mpMRI) and the Prostate Health Index (PHI) have allowed prediction of clinically significant prostate cancer (csPCa). Methods: To predict the likelihood of csPCa, we created a nomogram based on a multivariate model that included PHI and mpMRI. We assessed 315 males who were scheduled for prostate biopsies. Results: We used the Prostate Imaging Reporting and Data System version 2 (PI-RADS V2) to assess mpMRI and optimize PHI testing prior to biopsy. Univariate analysis showed that csPCa may be identified by PHI with a cut-off value of 77.77, PHID with 2.36, and PI-RADS with 3 as the best threshold. Multivariable logistic models for predicting csPCa were developed using PI-RADS, free PSA (fPSA), PHI, and prostate volume. A multivariate model that included PI-RADS, fPSA, PHI, and prostate volume had the best accuracy (AUC: 0.882). Decision curve analysis (DCA), which was carried out to verify the nomogram's clinical applicability, showed an ideal advantage (13.35% higher than the model that include PI-RADS only). Discussion: In conclusion, the nomogram based on PHI and mpMRI is a valuable tool for predicting csPCa while avoiding unnecessary biopsy as much as possible.

Nomograms for predicting progression-free survival and overall survival after surgery and concurrent chemoradiotherapy for glioblastoma: a retrospective cohort study.

BACKGROUND: Glioblastoma (GBM) is the most common malignant brain tumor in adults. The prognosis of GBM patients is poor. Even with active standard treatment, the median overall survival is only 14.6 months. It is therefore critical to ascertain recurrence and search for factors that influence the prognosis of GBM. This study aimed to screen the variables related to the progression-free survival (PFS) and overall survival (OS) of GBM patients undergoing surgery and concurrent chemoradiotherapy, as well as propose a nomogram for individual risk prediction based on preoperative imaging parameters and clinicopathological variables readily available in clinical practice. METHODS: We retrospectively analyzed 114 consecutive patients with GBM who underwent surgery and concurrent chemoradiotherapy at the Second Affiliated Hospital, Zhejiang University School of Medicine from January 1st, 2015, to June 1st, 2018. Twenty-four preoperative magnetic resonance imaging (MRI) parameters were extracted manually from the Picture Archiving and Communication System (PACS). Clinicopathological factors were extracted from the electronic medical record system (EMRS). Least absolute shrinkage and selection operator (LASSO) regression and Cox regression were used for feature selection and model prediction, respectively. The models were presented using nomograms, which were applied to identify the risk of recurrence and survival according to the score. The performance of the nomograms to predict PFS and OS was tested with C-statistics, calibration plots, and Kaplan-Meier curves. RESULTS: The results revealed that sex, Karnofsky performance score (KPS), O6-methylglucamine-DNA methyltransferase (MGMT) protein expression, number of adjuvant chemotherapy cycles with temozolomide (TMZ), and the MRI signature effectively predicted PFS; and sex, KPS, extent of surgery, number of TMZ cycles, and MRI signature effectively predicted OS. The nomogram revealed good discriminative ability (C-statistics: 0.81 for PFS and 0.79 for OS). In the nomogram of PFS, patients with a score greater than 122 were considered to have a high risk of recurrence. In the nomogram of OS, the cutoff score were 115 and 145, and then patients were classified as low, medium, and high risk. CONCLUSIONS: In conclusion, our nomograms can effectively predict the risk of recurrence and survival of GBM patients and thus can be a good guide for clinical practice.

A novel metabolic gene signature-based nomogram to predict overall survival in breast cancer.

BACKGROUND: Breast cancer risk prediction is often based on clinicopathological characteristics despite the high heterogeneity derived from gene expression. Metabolic alteration is a hallmark of cancer, and thus, the integration of a metabolic signature with clinical parameters is necessary to predict disease outcomes in breast cancers. METHODS: Metabolic genes were downloaded from the Gene Set Enrichment Analysis (GSEA) dataset. Genes with statistical significance in the univariate analysis were applied in the least absolute shrinkage and selection operator (LASSO) analysis to build a gene signature in the GSE20685 dataset. Clinicopathological characteristics and risk scores with prognostic significance were incorporated into the nomogram to predict the overall survival (OS) of patients. The Cancer Genome Atlas (TCGA) and GSE866166 datasets were used as the validation datasets. Time-dependent receiver operating characteristic (tROC) curves and calibration plots were used to assess the accuracy and discrimination of the model. RESULTS: A 55-gene metabolic gene signature (MGS) was constructed, and was significantly related to OS both in the discovery (P<0.001) and validation (P<0.001) datasets. The MGS was an independent prognostic factor and could divide patients into high- and low-risk groups regardless of their different prediction analysis of microarray 50 (PAM50) subtypes. Time-dependent ROC curves indicated that the risk scores based on the MGS [area under the ROC curve (AUC): 0.931] were superior to the those based on the American Joint Committee on Cancer (AJCC) stage (AUC: 0.781) and PAM50 (AUC: 0.675). A nomogram based on the AJCC stage and risk score could predict OS, and the calibration curves showed good agreement to the actual outcome, indicating that the nomogram may have practical utility. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis indicated that this MGS was primarily enriched in amino acid pathways. CONCLUSIONS: Our results demonstrated that the MGS was superior to existing risk predictors such as PAM50 and AJCC stage. By combining clinical factors (AJCC stage) and the MGS, a nomogram was constructed and showed good predictive ability for OS in breast cancer.

Building radiation-resistant model in triple-negative breast cancer to screen radioresistance-related molecular markers.

BACKGROUND: To build the triple-negative breast cancer (TNBC) radiation resistance model in vitro and vivo, and screen the molecular markers that related to radiation resistance. METHODS: We used X-ray to irradiate MDA-MB-231 cells repeatedly to build radioresistant cell (231-RR), then select one gemcitabine-resistance of MDA-MB-231 cell (231-GEM). We screen differentially expressed genes of these cell lines. Then, we would select 2 genes of them associated with DNA damage repair or cell cycle, and build RNAi lentivirus vector to knock down related gene. We also used X-rays repeatedly exposure TNBC tumor xenograft to build tumor with radioresistance properties, and then verify previously screening differentially expressed genes using IHC. Finally, we used The Cancer Genome Atlas (TCGA) database to validate the relationships between radioresistance related genes and the prognosis of breast cancer. RESULTS: We got 161 up-regulated genes and 156 down-regulated genes from three cell lines. Cellular results show the 231-cell with knock-down CDKN1A or SOD2 gene, its radiation sensitivity was significantly enhanced. We successfully got the TNBC xenograft tumor with radioresistance properties. Immunohistochemical results show that the radioresistance of tumor tissue with higher p21 (CDKN1A encoding protein) and SOD2 expression (P<0.01). The prognosis of patients with low SOD2 expression is better than that of high expression, but have no statistical significance (P=0.119); patients with low CDKN1A expression is significantly better than high expression (P=0.000). Multivariate cox analysis manifest that CDKN1A gene expression level is an independent prognostic factor in breast cancer patient (P=0.008). CONCLUSIONS: Construction of radiation resistance cell and xenograft tumor with radio-resistant properties model for radiation biology research is feasible. High SOD2 and CDKN1A is associated with the poor prognosis in breast cancer patients. These two genes could be used as a predicted makers of breast cancer radiation sensitivity.

The Definition and Delineation of the Target Area of Radiotherapy Based on the Recurrence Pattern of Glioblastoma After Temozolomide Chemoradiotherapy.

Radiotherapy is an important treatment for glioblastoma (GBM), but there is no consensus on the target delineation for GBM radiotherapy. The Radiation Therapy Oncology Group (RTOG) and European Organisation for Research and Treatment of Cancer (EORTC) each have their own rules. Our center adopted a target volume delineation plan based on our previous studies. This study focuses on the recurrence pattern of GBM patients whose target delineations did not intentionally include the T2/fluid-attenuated inversion recovery (FLAIR) hyperintensity area outside of the gross tumor volume (GTV). We prospectively collected 162 GBM cases and retrospectively analysed the clinical data and continuous dynamic magnetic resonance images (MRI) of 55 patients with recurrent GBM. All patients received concurrent radiotherapy and chemotherapy with temozolomide (TMZ). The GTV that we defined includes the postoperative T1-weighted MRI enhancement area and resection cavity. Clinical target volume 1 (CTV1) and CTV2 were defined as GTVs with 1 and 2 cm margins, respectively. Planning target volume 1 (PTV1) and PTV2 were defined as CTV1 and CTV2 plus a 3 mm margin with prescribed doses of 60 and 54 Gy, respectively. The first recurrent contrast-enhanced T1-weighted MRI was introduced into the Varian Eclipse radiotherapy planning system and fused with the original planning computed tomography (CT) images to determine the recurrence pattern. The median follow-up time was 15.8 months. The median overall survival (OS) and progression-free survival (PFS) were 17.7 and 7.0 months, respectively. Among the patients, 44 had central recurrences, two had in-field recurrences, one had marginal recurrence occurred, 11 had distant recurrences, and three had subependymal recurrences. Five patients had multiple recurrence patterns. Compared to the EORTC protocol, target delineation that excludes the adjacent T2/FLAIR hyperintensity area reduces the brain volume exposed to high-dose radiation (P = 0.000) without an increased risk of marginal recurrence. Therefore, it is worthwhile to conduct a clinical trial investigating the feasibility of intentionally not including the T2/FLAIR hyperintensity region outside of the GTV.

In-depth mining of clinical data: the construction of clinical prediction model with R.

This article is the series of methodology of clinical prediction model construction (total 16 sections of this methodology series). The first section mainly introduces the concept, current application status, construction methods and processes, classification of clinical prediction models, and the necessary conditions for conducting such researches and the problems currently faced. The second episode of these series mainly concentrates on the screening method in multivariate regression analysis. The third section mainly introduces the construction method of prediction models based on Logistic regression and Nomogram drawing. The fourth episode mainly concentrates on Cox proportional hazards regression model and Nomogram drawing. The fifth Section of the series mainly introduces the calculation method of C-Statistics in the logistic regression model. The sixth section mainly introduces two common calculation methods for C-Index in Cox regression based on R. The seventh section focuses on the principle and calculation methods of Net Reclassification Index (NRI) using R. The eighth section focuses on the principle and calculation methods of IDI (Integrated Discrimination Index) using R. The ninth section continues to explore the evaluation method of clinical utility after predictive model construction: Decision Curve Analysis. The tenth section is a supplement to the previous section and mainly introduces the Decision Curve Analysis of survival outcome data. The eleventh section mainly discusses the external validation method of Logistic regression model. The twelfth mainly discusses the in-depth evaluation of Cox regression model based on R, including calculating the concordance index of discrimination (C-index) in the validation data set and drawing the calibration curve. The thirteenth section mainly introduces how to deal with the survival data outcome using competitive risk model with R. The fourteenth section mainly introduces how to draw the nomogram of the competitive risk model with R. The fifteenth section of the series mainly discusses the identification of outliers and the interpolation of missing values. The sixteenth section of the series mainly introduced the advanced variable selection methods in linear model, such as Ridge regression and LASSO regression.

Highlights on molecular targets for radiosensitization of breast cancer cells: Current research status and prospects.

In the past, searching for effective radiotherapy sensitization molecular targets and improving the radiation sensitivity of malignant tumors was the hot topic for the oncologists, but with little achievements. We will summarize the research results about breast cancer irradiation sensitization molecular targets over the past two decades; we mainly focus on the following aspects: DNA damage repair and radiation sensitization, cell cycle regulation and radiation sensitization, cell autophagy regulation and radiation sensitization, and radiation sensitivity prediction and breast cancer radiotherapy scheme making. And based on this summary, we will put forward some of our viewpoints.

Dynamic evolution of Rayleigh-Taylor bubbles from sinusoidal, W-shaped, and random perturbations.

Implicit large eddy simulations of two-dimensional Rayleigh-Taylor instability at different density ratios (i.e., Atwood number A=0.05, 0.5, and 0.9) are conducted to investigate the late-time dynamics of bubbles. To produce a flow field full of bounded, semibounded, and chaotic bubbles, three problems with distinct perturbations are simulated: (I) periodic sinusoidal perturbation, (II) isolated W-shaped perturbation, and (III) random short-wave perturbations. The evolution of height h, velocity v, and diameter D of the (dominant) bubble with time t are formulated and analyzed. In problem I, during the quasisteady stage, the simulations confirm Goncharov's prediction of the terminal speed v_{∞}=Frsqrt[Agλ/(1+A)], where Fr=1/sqrt[3π]. Moreover, the diameter D at this stage is found to be proportional to the initial perturbation wavelength λ as D≈λ. This differed from Daly's simulation result of D=λ(1+A)/2. In problem II, a W-shaped perturbation is designed to produce a bubble environment similar to that of chaotic bubbles in problem III. We obtain a similar terminal speed relationship as above, but Fr is replaced by Fr_{w}≈0.63. In problem III, the simulations show that h grows quadratically with the bubble acceleration constant α≡h/(Agt^{2})≈0.05, and D expands self-similarly with a steady aspect ratio ß≡D/h≈(1+A)/2, which differs from existing theories. Therefore, following the mechanism of self-similar growth, we derive a relationship of ß=4α(1+A)/Fr_{w}^{2} to relate the evolution of chaotic bubbles in problem III to that of semibounded bubbles in problem II. The validity of this relationship highlights the fact that the dynamics of chaotic bubbles in problem III are similar to the semibounded isolated bubbles in problem II, but not to that of bounded periodic bubbles in problem I.

Prognostic factors in breast phyllodes tumors: a nomogram based on a retrospective cohort study of 404 patients.

The aim of this study was to explore the independent prognostic factors related to postoperative recurrence-free survival (RFS) in patients with breast phyllodes tumors (PTBs). A retrospective analysis was conducted in Fudan University Shanghai Cancer Center. According to histological type, patients with benign PTBs were classified as a low-risk group, while borderline and malignant PTBs were classified as a high-risk group. The Cox regression model was adopted to identify factors affecting postoperative RFS in the two groups, and a nomogram was generated to predict recurrence-free survival at 1, 3, and 5 years. Among the 404 patients, 168 (41.6%) patients had benign PTB, 184 (45.5%) had borderline PTB, and 52 (12.9%) had malignant PTB. Fifty-five patients experienced postoperative local recurrence, including six benign cases, 26 borderline cases, and 22 malignant cases; the three histological types of PTB had local recurrence rates of 3.6%, 14.1%, and 42.3%, respectively. Stromal cell atypia was an independent prognostic factor for RFS in the low-risk group, while the surgical approach and tumor border were independent prognostic factors for RFS in the high-risk group, and patients receiving simple excision with an infiltrative tumor border had a higher recurrence rate. A nomogram developed based on clinicopathologic features and surgical approaches could predict recurrence-free survival at 1, 3, and 5 years. For high-risk patients, this predictive nomogram based on tumor border, tumor residue, mitotic activity, degree of stromal cell hyperplasia, and atypia can be applied for patient counseling and clinical management. The efficacy of adjuvant radiotherapy remains uncertain.

Narrow-band imaging in the diagnosis of deep submucosal colorectal cancers: a systematic review and meta-analysis.

Background and aims Magnifying endoscopy with narrow-band imaging (M-NBI) has been widely used in the differential diagnosis of deep submucosal colorectal cancers (dSMCs) from superficial submucosal cancers (sSMCs) and intramucosal neoplasms. We aimed to pool the diagnostic efficacy of M-NBI and compare it with that of magnifying chromoendoscopy (M-CE) in diagnosing colorectal dSMC. Methods PubMed, EMBASE, and the Cochrane Library were searched to identify eligible studies. Meeting abstracts were also searched. A bivariate mixed-effects binary regression model was used in the meta-analysis to calculate the pooled diagnostic efficacy of M-NBI and compare it with that of M-CE in the diagnosis of dSMC. Subgroup analyses and meta-regression were conducted to explore sources of heterogeneity. Results We included 17 studies: 14 full texts and 3 meeting abstracts. The pooled sensitivity, specificity, and area under the summary receiver operating characteristic curve (AUC) with 95 % confidence intervals (CIs) in diagnosing dSMC were 74 % (66 % - 81 %; I2 = 84.6 %), 98 % (94 % - 99 %; I2 = 94.4 %), and 0.91 (0.88 - 0.93), respectively, for M-NBI. The pooled sensitivity, specificity and AUC (95 %CI) were 84 % (76 % - 89 %; I2 = 76.9 %), 97 % (94 % - 99 %; I2 = 90.2 %), and 0.97 (0.95 - 0.98), respectively, for M-CE. M-NBI had lower sensitivity (P < 0.01) than M-CE with similar specificity (P = 0.32). Subgroup analyses and meta-regression indicated that endoscopic diagnostic criteria, study type, endoscope type, risk of index test bias, and histopathological diagnostic criteria might be the sources of heterogeneity. Conclusions M-NBI and M-CE had comparable specificities in diagnosing dSMC, but the sensitivity of M-NBI was slightly lower than that of M-CE.

Validation of different staging systems for hepatocellular carcinoma in a cohort of 249 patients undergoing radiotherapy.

There is no consensus on predicting prognosis for hepatocellular carcinoma patients undergoing radiotherapy. This study aims to evaluate the validity of different staging systems. Overall, 249 hepatocellular carcinoma patients were evaluated retrospectively. All patients were classified by different staging systems. The cumulative survival rates were calculated using the Kaplan-Meier method, and survival curves were compared using the log-rank test. Harrell's concordance index (c-index) was calculated. The 1-, 3-, and 5-year overall survival rates were 58%, 31% and 20%, respectively. Significant differences in overall survival were observed between stages I and II of the Okuda staging system (p=0.004), between scores of 3 and 4 of Cancer of the Liver Italian Program prognostic score (p=0.009), between Chinese University Prognostic Index low-risk and intermediate-risk groups (p=0.01), between 1 and 2 points of the Japan Integrated Staging score (p=0.037), between stages III and IV of American Joint Committee on Cancer 1997 TNM staging system (p=0.011), between stages II and III of American Joint Committee on Cancer 2002 TNM staging system (p=0.026) and between stages I and II of Guangzhou 2001 staging system (p=0.000). In conclusion, the Okuda staging system, Chinese University Prognostic Index, and Chinese Guangzhou 2001 staging system were more discriminative than the other staging systems in the prognostic stratification for hepatocellular carcinoma patients undergoing radiotherapy.

The Chk1 inhibitor MK-8776 increases the radiosensitivity of human triple-negative breast cancer by inhibiting autophagy.

MK-8776 is a recently described inhibitor that is highly selective for checkpoint kinase 1 (Chk1), which can weaken the DNA repair capacity in cancer cells to achieve chemo-sensitization. A number of studies show that MK-8776 enhances the cytotoxicity of hydroxyurea and gemcitabine without increasing normal tissue toxicities. Thus far, there is no evidence that MK-8776 can be used as a radiotherapy sensitization agent. In this study, we investigated the effects of MK-8776 on the radiosensitivity of 3 human triple-negative breast cancer (TNBC) cell lines MDA-MB-231, BT-549 and CAL-51. MK-8776 dose-dependently inhibited the proliferation of MDA-MB-231, BT-549 and CAL-51 cells with IC50 values of 9.4, 17.6 and 2.1 µmol/L, respectively. Compared with irradiation-alone treatment, pretreatment with a low dose of MK-8776 (100-400 nmol/L) significantly increased irradiation-induced γH2A.X foci in the 3 TNBC cell lines, suggesting enhanced DNA damage by MK-8776, inhibited the cell proliferation and increased the radiosensitivity of the 3 TNBC cell lines. Similar results were obtained in MDA-MB-231 xenograft tumors in nude mice that received MK-8776 (15 or 40 mg/kg, ip) 26 d after irradiation. To explore the mechanisms underlying the radio-sensitization by MK-8776, we used TEM and found that irradiation significantly increased the numbers of autophagosomes in the 3 TNBC cell lines. Moreover, irradiation markedly elevated the levels of Atg5, and promoted the transformation of LC3-I to LC3-II in the cells. Pretreatment with the low dose of MK-8776 suppressed these effects. The above results suggest that MK-8776 increases human TNBC radiosensitivity by inhibiting irradiation-induced autophagy and that MK-8776 may be a potential agent in the radiosensitization of human TNBC.

Genetic epidemiology of amyotrophic lateral sclerosis: a systematic review and meta-analysis.

BACKGROUND: Genetic studies have shown that C9orf72, SOD1, TARDBP and FUS are the most common mutated genes in amyotrophic lateral sclerosis (ALS). Here, we performed a meta-analysis to determine the mutation frequencies of these major ALS-related genes in patients with ALS. METHODS: We performed an extensive literature research to identify all original articles reporting frequencies of C9orf72, SOD1, TARDBP and FUS mutations in ALS. The mutation frequency and effect size of each study were combined. Possible sources of heterogeneity across studies were determined by meta-regression, sensitivity analysis and subgroup analysis. RESULTS: 111 studies were included in the meta-analysis. The overall pooled mutation frequencies of these major ALS-related genes were 47.7% in familial amyotrophic lateral sclerosis (FALS) and 5.2% in sporadic ALS (SALS). A significant difference was identified regarding the frequencies of mutations in major ALS genes between European and Asian patients. In European populations, the most common mutations were the C9orf72 repeat expansions (FALS 33.7%, SALS 5.1%), followed by SOD1 (FALS 14.8%, SALS 1.2%), TARDBP (FALS 4.2%, SALS 0.8%) and FUS mutations (FALS 2.8%, SALS 0.3%), while in Asian populations the most common mutations were SOD1 mutations (FALS 30.0%, SALS 1.5%), followed by FUS (FALS 6.4%, SALS 0.9%), C9orf72 (FALS 2.3%, SALS 0.3%) and TARDBP (FALS 1.5%, SALS 0.2%) mutations. CONCLUSIONS: These findings demonstrated that the genetic architecture of ALS in Asian populations is distinct from that in European populations, which need to be given appropriate consideration when performing genetic testing of patients with ALS.

Dosimetric factors and Lyman normal-tissue complication modelling analysis for predicting radiation-induced lung injury in postoperative breast cancer radiotherapy: a prospective study.

To investigate the relationship between dosimetric factors, including Lyman normal-tissue complication (NTCP) parameters and radiation-induced lung injury (RILI), in postoperative breast cancer patients treated by intensity modulated radiotherapy (IMRT). 109 breast cancer patients who received IMRT between January 2012 and December 2013 were prospectively enrolled. A maximum likelihood analysis yielded the best estimates for Lyman NTCP parameters. Ten patients were diagnosed with RILI (primarily Grade 1 or Grade 2 RILI); the rate of RILI was 9.17% (10/109). Multivariate analysis demonstrated that ipsilateral lung V20 was an independent predictor (P=0.001) of RILI. Setting V20=29.03% as the cut-off value, the prediction of RILI achieved high accuracy (94.5%), with a sensitivity of 80% and specificity of 96%. The NTCP model parameters for 109 patients were m=0.437, n=0.912, and TD50(1)=17.211 Gy. The sensitivity of the modified Lyman NTCP model to predict the RILI was 90% (9/10), the specificity was 69.7% (69/99), and the accuracy was 71.6% (78/109). The RILI rate of the NTCP<9.62% in breast cancer patients was 1.43% (1/70), but the RILI rate of the NTCP>9.62% in patients with breast cancer was 23.08% (9/39), (P=0.001). In conclusion, V20 is an independent predictive factor for RILI in patients with breast cancer treated by IMRT; V20=29.03% could be a useful dosimetric parameter to predict the risk of RILI. The Lyman NTCP model parameters of the new value (m=0.437, n=0.912, TD50 (1) =17.211 Gy) can be used as an effective biological index to evaluate the risk of RILI.

Fluorouracil-based neoadjuvant chemoradiotherapy with or without oxaliplatin for treatment of locally advanced rectal cancer: An updated systematic review and meta-analysis.

To measure the safety and efficacy of oxaliplatin (OX) application in neoadjuvant chemoradiotherapy (CRT) for locally advanced rectal cancer (LARC), EMBASE, PubMed, Cochrane Library, and Web of Science were used for a literature search. Cochrane's risk of bias tool of randomized controlled trials (RCTs) was used for quality evaluation. The statistical analyses were performed using RevMan 5.3. In addition, 95% confidence intervals (CIs) and pooled risk ratios (RRs) were calculated. Seven RCTs were included in our meta-analysis. After adding OX to fluoropyrimidine (FU), a marginal significant improvement in disease-free survival was noted compared with FU alone (RR = 0.89, 95% CI: 0.78-1.00; P = 0.05). Neoadjuvant CRT with OX significantly decreased the distant metastasis rate (RR = 0.79, 95% CI: 0.67-0.94, P = 0.007). However, no improvement in the local recurrence rate (RR = 0.86, 95% CI: 0.68-1.08; P = 0.19) was noted. In addition, neoadjuvant CRT with OX also significantly increased the pathologic complete response (RR = 1.24, 95% CI: 1.02-1.51; P = 0.03). Grade 3-4 acute toxicity and grade 3-4 diarrhea was considerably higher for OX/FU compared with FU alone. In conclusion, the use of OX on the basis of FU/capecitabine in preoperative CRT is feasible. LARC patients are likely to benefit from CRT regimens with OX.

PSCA polymorphisms and gastric cancer susceptibility in an eastern Chinese population.

The prostate stem cell antigen (PSCA) gene, which encodes a prostate-specific antigen (PSA), was identified as a gene involved in cell adhesion and proliferation. The associations between the PSCA rs2294008 and rs2976392 single nucleotide polymorphisms (SNPs) and gastric cancer (GCa) susceptibility were still controversial. To derive a more precise estimation of the associations, we conducted a case-control study of 1,124 cases and 1,192 controls in an eastern Chinese population. We found that the rs2294008T variant genotypes were associated with an increased GCa risk in this study population (CT vs CC, OR=1.59, 95% CI=1.33-1.89 and CT+TT vs CC, OR=1.38, 95% CI=1.17-1.62). For SNP rs2976392, the variant A genotypes were also associated with an increased GCa risk (AG vs GG, OR=1.61, 95% CI=1.35-1.91 and AG+AA vs GG, OR=1.47, 95% CI=1.25-1.74). The results were further validated by a meta-analysis. In conclusion, the results indicated that the PSCA rs2294008 T and rs2976392 A alleles were low-penetrate risk factors for GCa in this study population. However, large and well-designed studies are warranted to validate our findings.

Diagnostic performance of core needle biopsy in identifying breast phyllodes tumors.

BACKGROUND: A retrospective analysis of diagnoses was performed in patients with phyllodes tumors of the breast (PTB) who received preoperative core needle biopsy (CNB) and had breast surgery at Fudan University Shanghai Cancer Center from January 1, 2002 to April 1, 2013. The resulting data allowed us to compare the accordance between CNB and excision diagnoses of PTB patients and evaluate the accuracy of CNB in preoperative diagnosis. METHODS: Data from 128 patients with PTB who had undergone preoperative CNB and breast surgery were retrospectively analyzed. We reviewed the medical history, clinical follow-up data, and CNB diagnostic data. A diagnostic test was used to evaluate the sensitivity and specificity of CNB in diagnosing benign, borderline, and malignant phyllodes tumors. RESULTS: The accuracy of CNB for diagnosing PTB was 13.3% (17/128). Of the remaining patients, 98 (75.5% of the PTB patients) were diagnosed with fibroadenoma or fibroepithelial lesions. The sensitivity of CNB at diagnosing benign, borderline, and malignant phyllodes tumors were 4.9% (2/41), 4.2% (3/71), and 25.0% (4/16), respectively, whereas the corresponding specificity were 92.0%, 98.2%, and 100%, respectively. Some clinical features, such as large tumor size, rapid growth, or surgical history of fibroadenomas, were indicative of an increased possibility of PTB. CONCLUSIONS: CNB provides a pathological basis for the preoperative diagnosis of PTB, but it has a poor accuracy and offers limited guidance for surgical decisions. Considering CNB along with multiple histologic features may improve the ability to accurately diagnose PTB. An integrated assessment using CNBs in combination with clinical data and imaging features is suggested as a reliable strategy to assist PTB diagnosis.

Did dose escalated radiotherapy in stage III non-small cell lung cancer improve overall survival?

Radiotherapy has been applied in the treatment for lung cancer patients for many years, especially those with advanced stage disease who cannot be treated with surgery. However, if these advanced stage patients should be treated with standard dosage therapy (60 Gy) or high dosage therapy (>60 Gy) remains a hot debated point. Literature related to this topic would be reviewed here. We believe standard dosage therapy should be strongly recommended, and high dosage therapy might benefit patients with high risk factors patients.