Clinical outcomes of second-line chemotherapy in patients with advanced pancreatic adenocarcinoma:a real-world study

Objective:Little progress has been made in recent years using first-line chemotherapy,including gemcitabine combined with nab-paclitaxel,FOLFIRINOX,and NALIRIFOX,for advanced pancreatic adenocarcinoma(APC).In addition,the optimal second-line chemotherapy regimen has not been determined.This study aimed to compare the effectiveness of different types of second-line chemotherapy for APC.Methods:Patients with APC who received first-line treatment from January 2008 to January 2021 were considered eligible for this retrospective analysis.The primary and secondary endpoints were overall survival(OS)and progression-free survival(PFS),respectively.Results:Four hundred and thirty-seven and 617 patients were treated with 5-fluorouracil-and gemcitabine-based chemotherapy as first-line treatment,respectively.Demographic and clinical features,except age and liver metastasis,were comparable between the two groups(P<0.05).The median OS was 8.8 and 7.8 months in patients who received a 5-fluorouracil-and gemcitabine-based combined regimen for first-line therapy,respectively(HR=1.244,95%CI=1.090–1.419;P<0.001).The median OS was 5.6 and 1.9 months in patients who received second-line chemotherapy and supportive care,respectively(HR=0.766,95%CI=0.677–0.867;P<0.001).The median PFS was not significantly differently between gemcitabine or 5-fluorouracil monotherapy and combination therapy.Conclusions:A 5-fluorouracil-or gemcitabine-based combined regimen was shown to be as effective as a single 5-fluorouracil or gemcitabine regimen as second-line therapy for patients with APC.

Utilization of Real-World Data in Drug Development

With the rapid development of modern science and technology, traditional randomized controlled trials have become insufficient to meet current scientific research needs, particularly in the field of clinical research. The emergence of real-world data studies, which align more closely with actual clinical evidence, has garnered significant attention in recent years. The following is a brief overview of the specific utilization of real-world data in drug development, which often involves large sample sizes and analyses covering a relatively diverse population without strict inclusion and exclusion criteria. Real-world data often reflects real clinical practice: treatment options are chosen according to the actual conditions and willingness of patients rather than through random assignment. Analysis based on real-world data also focuses on endpoints highly relevant to clinical benefits and the quality of life of patients. The booming big data technology supports the utilization of real-world data to accelerate new drug development, serving as an important supplement to traditional clinical trials.

Quantitative Comparative Study of the Performance of Lossless Compression Methods Based on a Text Data Model

Data compression plays a key role in optimizing the use of memory storage space and also reducing latency in data transmission. In this paper, we are interested in lossless compression techniques because their performance is exploited with lossy compression techniques for images and videos generally using a mixed approach. To achieve our intended objective, which is to study the performance of lossless compression methods, we first carried out a literature review, a summary of which enabled us to select the most relevant, namely the following: arithmetic coding, LZW, Tunstall’s algorithm, RLE, BWT, Huffman coding and Shannon-Fano. Secondly, we designed a purposive text dataset with a repeating pattern in order to test the behavior and effectiveness of the selected compression techniques. Thirdly, we designed the compression algorithms and developed the programs (scripts) in Matlab in order to test their performance. Finally, following the tests conducted on relevant data that we constructed according to a deliberate model, the results show that these methods presented in order of performance are very satisfactory:- LZW- Arithmetic coding- Tunstall algorithm- BWT + RLELikewise, it appears that on the one hand, the performance of certain techniques relative to others is strongly linked to the sequencing and/or recurrence of symbols that make up the message, and on the other hand, to the cumulative time of encoding and decoding.

Comparison of two statistical methods for handling missing values of quantitative data in Bayesian N-of-1 trials: a simulation study

Background:Missing data are frequently occurred in clinical studies.Due to the development of precision medicine,there is an increased interest in N-of-1 trial.Bayesian models are one of main statistical methods for analyzing the data of N-of-1 trials.This simulation study aimed to compare two statistical methods for handling missing values of quantitative data in Bayesian N-of-1 trials.Methods:The simulated data of N-of-1 trials with different coefficients of autocorrelation,effect sizes and missing ratios are obtained by SAS 9.1 system.The missing values are filled with mean filling and regression filling respectively in the condition of different coefficients of autocorrelation,effect sizes and missing ratios by SPSS 25.0 software.Bayesian models are built to estimate the posterior means by Winbugs 14 software.Results:When the missing ratio is relatively small,e.g.5%,missing values have relatively little effect on the results.Therapeutic effects may be underestimated when the coefficient of autocorrelation increases and no filling is used.However,it may be overestimated when mean or regression filling is used,and the results after mean filling are closer to the actual effect than regression filling.In the case of moderate missing ratio,the estimated effect after mean filling is closer to the actual effect compared to regression filling.When a large missing ratio(20%)occurs,data missing can lead to significantly underestimate the effect.In this case,the estimated effect after regression filling is closer to the actual effect compared to mean filling.Conclusion:Data missing can affect the estimated therapeutic effects using Bayesian models in N-of-1 trials.The present study suggests that mean filling can be used under situation of missing ratio≤10%.Otherwise,regression filling may be preferable.

Meta-analysis with zero-event studies:a comparative study with application to COVID-19 data

Background:Meta-analysis is a statistical method to synthesize evidence from a number of independent studies,including those from clinical studies with binary outcomes.In practice,when there are zero events in one or both groups,it may cause statistical problems in the subsequent analysis.Methods:In this paper,by considering the relative risk as the effect size,we conduct a comparative study that consists of four continuity correction methods and another state-of-the-art method without the continuity correction,namely the generalized linear mixed models(GLMMs).To further advance the literature,we also introduce a new method of the continuity correction for estimating the relative risk.Results:From the simulation studies,the new method performs well in terms of mean squared error when there are few studies.In contrast,the generalized linear mixed model performs the best when the number of studies is large.In addition,by reanalyzing recent coronavirus disease 2019(COVID-19)data,it is evident that the double-zero-event studies impact the estimate of the mean effect size.Conclusions:We recommend the new method to handle the zero-event studies when there are few studies in a meta-analysis,or instead use the GLMM when the number of studies is large.The double-zero-event studies may be informative,and so we suggest not excluding them.

On the Combination of “The Textual Research on Historical Documents” and “The Comparative Study of Historical Data” —— and a Discussion on “The Law of Quan-ma and Gui-mei” in Chinese Language Studies

In Chinese language studies, both “The Textual Research on Historical Documents” and “The Comparative Study of Historical Data” are traditional in methodology and they both deserve being treasured, passed on, and further developed. It will certainly do harm to the development of academic research if any of the two methods is given unreasonable priority. The author claims that the best or one of the best methodologies of the historical study of Chinese language is the combination of the two, hence a new interpretation of “The Double-proof Method”. Meanwhile, this essay is also an attempt to put forward “The Law of Quan-ma and Gui-mei” in Chinese language studies, in which the author believes that it is not advisable to either treat Gui-mei as Quan-ma or vice versa in linguistic research. It is crucial for us to respect always the language facts first, which is considered the very soul of linguistics.

Research on Retrospective Studies of Real-World Study and Its Selection Bias

Objective To provide references for improving the authenticity and reliability of the retrospective study results,thus improving the quality of evidence in the real world and strengthening drug supervision and decision-making.Methods Literature review was used to study the data sources,the characteristics of retrospective research,the sources and the corrections of selective bias in the real world.Results and Conclusion The biases in retrospective study mainly come from admission rate bias,patient rate bias,survivors bias,health user bias and symptom bias.

Experimental Design of Observational Studies in Real-World Study

Objective To introduce the design of observational trials under real-world study(RWS),and to provide guidance for clinical development of new research trials and reference for real-world researchers.Methods Relevant literature of RWS and observational experiments at home and abroad were reviewed and analyzed,and then the design of observational studies was summarized under RWS.Results and Conclusion The data and information provided in observational studies not only help to further verify the clinical study results obtained by randomized controlled trial(RCT)in clinical practice,but also objectively reflect the real situation in the process of clinical research and application.

Question classification in question answering based on real-world web data sets

To improve question answering （QA） performance based on real-world web data sets,a new set of question classes and a general answer re-ranking model are defined.With pre-defined dictionary and grammatical analysis,the question classifier draws both semantic and grammatical information into information retrieval and machine learning methods in the form of various training features,including the question word,the main verb of the question,the dependency structure,the position of the main auxiliary verb,the main noun of the question,the top hypernym of the main noun,etc.Then the QA query results are re-ranked by question class information.Experiments show that the questions in real-world web data sets can be accurately classified by the classifier,and the QA results after re-ranking can be obviously improved.It is proved that with both semantic and grammatical information,applications such as QA, built upon real-world web data sets, can be improved,thus showing better performance.

Efficacy and safety of lenvatinib for patients with advanced hepatocellular carcinoma: A retrospective, real-world study conducted in China

BACKGROUND Lenvatinib has become an indispensable part of treatment regimens for patients with advanced hepatocellular carcinoma(aHCC).Several recent real-world studies appear to have confirmed this;however,there are etiological differences.This necessitates further real-world studies of lenvatinib across diverse populations,such as in China.AIM To investigate the efficacy and safety of lenvatinib in a Chinese HCC patient population under real-world conditions.METHODS This is a retrospective and multiregional study involving patients with aHCC receiving lenvatinib monotherapy.Efficacy was assessed using the Response Evaluation Criteria in Solid Tumors version 1.1.Baseline characteristics and adverse events(AEs)were recorded throughout the entire study.RESULTS In total,54 HCC patients treated with lenvatinib monotherapy were included for final analysis.The objective response rate was 22%(n=12)with a progressionfree survival(PFS)of 168 d;however,AEs occurred in 92.8%of patients.Multivariate analysis showed that the Barcelona Clinic Liver Cancer stage[hazard ratio(HR)0.465;95%CI:0.23-0.93;P=0.031],portal vein tumor thrombus(HR 0.38;95%CI:0.15-0.94;P=0.037)and Child-Pugh classifications(HR 0.468;95%CI:and specificity(83.3%)of decreasing serum biomarkers including alphafetoprotein were calculated in order to predict tumor size reduction.Gene sequencing also provided insights into potential gene mutation signatures related to the effect of lenvatinib.CONCLUSION Our findings confirm previous evidence from the phase III REFLECT study.The majority of patients in this Chinese sample were suffering from concomitant hepatitis B virus-related HCC.However,further analysis suggested that baseline characteristics,changes in serum biomarkers and gene sequencing may hold the key for predicting lenvatinib responses.Further large-scale prospective studies that incorporate more basic medical science measures should be conducted.

Clinical outcomes of atezolizumab in combination with etoposide/platinum for treatment of extensive-stage small-cell lung cancer:A real-world,multicenter,retrospective,controlled study in China

Objective:Atezolizumab along with chemotherapy has prolonged the survival of patients with extensive-stage small-cell lung cancer(ES-SCLC)worldwide,although real-world(RW)data are lacking in China.This study was designed to evaluate the efficacy and clinical outcomes of atezolizumab plus etoposide/platinum(EP).Methods:Data obtained in this retrospective study were captured from six oncology units of five medical facilities from January 2019 to April 2022.For first-line treatments,atezolizumab combined with EP vs.EP alone,we primarily evaluated progression-free survival(PFS);other efficacy indicators,including overall survival(OS),objective response rate(ORR),and patterns of SCLC progression and adverse events(AEs)were assessed.Results:The primary analysis included data from 225 patients,of whom 133 received EP along with atezolizumab(atezolizumab group)and 92 received EP alone(EP group).The PFS duration of the atezolizumab group[7.10 months;95%confidence interval(95%CI),6.53-9.00]exceeded that of the EP group(6.50 months;95%CI,4.83-7.53).Overall,the hazard ratio(HR)was 0.69(95%CI,0.49-0.97)(P=0.029);particularly,the HR was 0.54(95%CI,0.36-0.80)among patients undergoing≥4 chemotherapy cycles and 0.33(95%CI,0.20-0.56)among individuals with atezolizumab maintenance.The ORR and disease-control rate(DCR)were similar between the two groups.Because of incomplete OS data,the median OS was not determined for either group.Bone marrow suppression was the most common AE detected(58.6%)in the atezolizumab group.Immune-related AEs occurred in 19 patients in the atezolizumab group(14.3%),with only one case of grade 3 encephalitis.Conclusions:This RW study in China demonstrated improved clinical outcomes of atezolizumab along with EP for ES-SCLC,particularly in the chemosensitive population.These results align with the results of the IMpower133 study,although the impact of this treatment modality on OS warrants additional follow-up studies.

Snow and sea ice thermodynamics in the Arctic:Model validation and sensitivity study against SHEBA data

Evolution of the Arctic sea ice and its snow cover during the SHEBA year were simulated by applying a high-resolution thermodynamic snow/ice model （HIGHTSI）. Attention was paid to the impact of albedo on snow and sea ice mass balance, effect of snow on total ice mass balance, and the model vertical resolution. The SHEBA annual simulation was made applying the best possible external forcing data set created by the Sea Ice Model Intercomparison Project. The HIGHTSI control run reasonably reproduced the observed snow and ice thickness. A number of albedo schemes were incorporated into HIGHTSI to study the feedback processes between the albedo and snow and ice thickness. The snow thickness turned out to be an essential variable in the albedo parameterization. Albedo schemes dependent on the surface temperature were liable to excessive positive feedback effects generated by errors in the modelled surface temperature. The superimposed ice formation should be taken into account for the annual Arctic sea ice mass balance.

A study of anchoring geographic coordinates and calculating zenith and azimuth of sun and scanner for oceanic satellite data

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A Case Study of Impact of FY-2C Satellite Data in Cloud Analysis to Improve Short-Range Precipitation Forecast

Chinese FengYun-2C(FY-2C) satellite data were combined into the Local Analysis and Prediction System(LAPS) model to obtain three-dimensional cloud parameters and rain content. These parameters analyzed by LAPS were used to initialize the Global/Regional Assimilation and Prediction System model(GRAPES) in China to predict precipitation in a rainstorm case in the country. Three prediction experiments were conducted and were used to investigate the impacts of FY-2C satellite data on cloud analysis of LAPS and on short range precipitation forecasts. In the first experiment, the initial cloud fields was zero value. In the second, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS without combining the satellite data. In the third experiment, the initial cloud fields were cloud liquid water, cloud ice, and rain content derived from LAPS including satellite data. The results indicated that the FY-2C satellite data combination in LAPS can show more realistic cloud distributions, and the model simulation for precipitation in 1–6 h had certain improvements over that when satellite data and complex cloud analysis were not applied.

Constructing Large Scale Cohort for Clinical Study on Heart Failure with Electronic Health Record in Regional Healthcare Platform:Challenges and Strategies in Data Reuse

Regional healthcare platforms collect clinical data from hospitals in specific areas for the purpose of healthcare management.It is a common requirement to reuse the data for clinical research.However,we have to face challenges like the inconsistence of terminology in electronic health records (EHR) and the complexities in data quality and data formats in regional healthcare platform.In this paper,we propose methodology and process on constructing large scale cohorts which forms the basis of causality and comparative effectiveness relationship in epidemiology.We firstly constructed a Chinese terminology knowledge graph to deal with the diversity of vocabularies on regional platform.Secondly,we built special disease case repositories (i.e.,heart failure repository) that utilize the graph to search the related patients and to normalize the data.Based on the requirements of the clinical research which aimed to explore the effectiveness of taking statin on 180-days readmission in patients with heart failure,we built a large-scale retrospective cohort with 29647 cases of heart failure patients from the heart failure repository.After the propensity score matching,the study group (n=6346) and the control group (n=6346) with parallel clinical characteristics were acquired.Logistic regression analysis showed that taking statins had a negative correlation with 180-days readmission in heart failure patients.This paper presents the workflow and application example of big data mining based on regional EHR data.

Facilitating transparency in spinal cord injury studies using data standards and ontologies

Progress in developing robust therapies for spinal cord injury （SCI）, trau- matic brain injury （TBI） and peripheral nerve injury has been slow. A great deal has been learned over the past 30 years regarding both the intrinsic factors and the environmental factors that regulate axon growth, but this large body of information has not yet resulted in clinically available thera- peutics. This therapeutic bottleneck has many root causes, but a consensus is emerging that one contributing factor is a lack of standards for experi- mental design and reporting. The absence of reporting standards, and even of commonly accepted definitions of key words, also make data mining and bioinformatics analysis of neural plasticity and regeneration difficult, if not impossible. This short review will consider relevant background and poten- tial solutions to this problem in the axon regeneration domain.

Effectiveness of second-line anti-HER2 treatment in HER2-positive metastatic breast cancer patients previously treated with trastuzumab:A real-world study

Objective:Several studies have demonstrated different benefits for patients whose disease progressed despite previous trastuzumab treatment.Due to limited real-world data,we evaluate the effectiveness of anti-human epidermal growth factor receptor 2(HER2)therapy(lapatinib or trastuzumab)plus chemotherapy or chemotherapy alone in patients who were previously treated with trastuzumab-containing regimens and investigate factors associated with effectiveness.And we further show the effectiveness of the two anti-HER2 therapy groups.Methods:A total of 342 HER2-positive metastatic breast cancer(MBC)patients whose disease progressed during prior anti-HER2(trastuzumab)and standard chemotherapy therapy from Department of Breast Oncology,the Fifth Medical Center of Chinese PLA General Hospital,from August 2010 to December 2016 were included.Seventy-eight patients received standard chemotherapy only,148 patients continued to receive trastuzumab and switched to other chemotherapy drugs,and 116 patients received tyrosine-kinase inhibitors(TKIs;lapatinib)and chemotherapy.The main outcome measures were progression-free survival(PFS),overall response rate(ORR),and clinical benefit rate(CBR).Subgroup analyses were conducted to identify patient characteristics associated with the greatest clinical benefit.Results:After a median follow-up of 26.2(range,2.0-56.0)months,PFS significantly improved with anti-HER2 therapy compared with chemotherapy alone:median 6.0 months with lapatinib[95%confidence interval(95%CI),4.53-7.47],4.5 months with trastuzumab(95%CI,3.99-5.01)vs.3.0 months with chemotherapy alone(95%CI,2.42-3.58);stratified hazard ratio(HR)=0.70,95%CI,0.60-0.81;P<0.0001.The ORR values were 33.6%,25.0%and 12.8%,respectively,the CBR values were 60.3%,48.6%and 26.9%,respectively.The effectiveness of lapatinib group and trastuzumab group were further analyzed.In multivariate analysis,lapatinib group was associated with a longer PFS,after controlling other potential confounders(HR=0.68,95%CI,0.52-0.90;P=0.006).Conclusions:The combination of TKIs and chemotherapy was effective in this cohort previously treated with trastuzumab treatment.Therefore,TKIs combined with chemotherapy is an option for Chinese HER2-positive MBC patients previously treated with trastuzumab treatment.

Real-world 10-year retrospective study of the guidelines for diagnosis and treatment of primary liver cancer in China

BACKGROUND Hepatocellular carcinoma(HCC) is a common malignant tumor worldwide. Many regions across the world have issued various HCC diagnosis and treatment protocols to improve the diagnosis and targeted treatment of patients with HCC. However, real-world studies analysing the practice, application value, and existing problems of the China Liver Cancer(CNLC) staging system are scarce.AIM To analyze the current situation and problems associated with the Guidelines for Diagnosis and Treatment of Primary Liver Cancer in China.METHODS We collected the medical records of all patients with HCC admitted to the First Affiliated Hospital of Zhengzhou University from January 1, 2011 to December 31, 2019, and recorded the hospitalization information of those patients until December 31, 2020. All information on the diagnosis and treatment of the target patients was recorded, and their demographic and sociological characteristics, CNLC stages, screening situations, and treatment methods and effects were analyzed. The survival status of the patients was obtained from follow-up data.RESULTS This study included the medical records of 3022 patients with HCC. Among these cases, 304 patients were screened before HCC diagnosis;their early-stage diagnosis rate was 69.08%, which was significantly higher than that of patients with HCC who were diagnosed without screening and early detection(33.74%). Herein, patients with no clinical outcome at discharge were followed up, and the survival information of 1128 patients was obtained. A Cox model was used to analyse independent risk factors affecting overall survival, which were revealed as age > 50 years, no screening, alpha-fetoprotein > 400 ng/mL, Child–Pugh grade B, and middle and late CNLC stages. Based on the Cox model survival analysis, in our study, patients with HCC identified via screening had significant advantages in overall and tumorfree survival after hepatectomy.CONCLUSION Early diagnosis and treatment can be achieved by screening groups at high risk for HCC based on the guidelines;however, real-world compliance is poor.

Commentary on:“Facilitating transparency in spinal cord injury studies using data standards and ontologies”

Commentary Most would agree that providing comprehensive detail in scientific reporting is critical for the development of mean- ingful therapies and treatments for diseases. Such stellar practices 1） allow for reproduction of experiments to con- firm results, 2） promote thorough analyses of data, and 3） foster the incremental advancement of valid approaches. Unfortunately, most would also agree we have far to go to reach this vital goal （Hackam and Redelmeier, 2006; Prinz et al., 2011; Baker et al., 2014）.

Immunotherapy for advanced hepatocellular carcinoma:From clinical trials to real-world data and future advances

Hepatocellular carcinoma(HCC)is a leading cause of cancer-associated mortality worldwide.HCC is an inflammation-associated immunogenic cancer that frequently arises in chronically inflamed livers.Advanced HCC is managed with systemic therapies;the tyrosine kinase inhibitor(TKI)sorafenib has been used in 1st-line setting since 2007.Immunotherapies have emerged as promising treatments across solid tumors including HCC for which immune checkpoint inhibitors(ICIs)are licensed in 1st-and 2nd-line treatment setting.The treatment field of advanced HCC is continuously evolving.Several clinical trials are investigating novel ICI candidates as well as new ICI regimens in combination with other therapeutic modalities including systemic agents,such as other ICIs,TKIs,and anti-angiogenics.Novel immunotherapies including adoptive cell transfer,vaccine-based approaches,and virotherapy are also being brought to the fore.Yet,despite advances,several challenges persist.Lack of real-world data on the use of immunotherapy for advanced HCC in patients outside of clinical trials constitutes a main limitation hindering the breadth of application and generalizability of data to this larger and more diverse patient cohort.Consequently,issues encountered in real-world practice include patient ineligibly for immunotherapy because of contraindications,comorbidities,or poor performance status;lack of response,efficacy,and safety data;and cost-effectiveness.Further real-world data from high-quality large prospective cohort studies of immunotherapy in patients with advanced HCC is mandated to aid evidence-based clinical decision-making.This review provides a critical and comprehensive overview of clinical trials and real-world data of immunotherapy for HCC,with a focus on ICIs,as well as novel immunotherapy strategies underway.