Omics-imaging signature-based nomogram to predict the progression-free survival of patients with hepatocellular carcinoma after transcatheter arterial chemoembolization

BACKGROUND Enhanced magnetic resonance imaging(MRI)is widely used in the diagnosis,treatment and prognosis of hepatocellular carcinoma(HCC),but it can not effectively reflect the heterogeneity within the tumor and evaluate the effect after treatment.Preoperative imaging analysis of voxel changes can effectively reflect the internal heterogeneity of the tumor and evaluate the progression-free survival(PFS).AIM To predict the PFS of patients with HCC before operation by building a model with enhanced MRI images.METHODS Delineate the regions of interest(ROI)in arterial phase,portal venous phase and delayed phase of enhanced MRI.After extracting the combinatorial features of ROI,the features are fused to obtain deep learning radiomics(DLR)_Sig.DeLong's test was used to evaluate the diagnostic performance of different typological features.K-M analysis was applied to assess PFS in different risk groups,and the discriminative ability of the model was evaluated using the Cindex.RESULTS Tumor diameter and diolame were independent factors influencing the prognosis of PFS.Delong's test revealed multi-phase combined radiomic features had significantly greater area under the curve values than did those of the individual phases(P<0.05).In deep transfer learning(DTL)and DLR,significant differences were observed between the multi-phase and individual phases feature sets(P<0.05).K-M survival analysis revealed a median survival time of high risk group and low risk group was 12.8 and 14.2 months,respectively,and the predicted probabilities of 6 months,1 year and 2 years were 92%,60%,40%and 98%,90%,73%,respectively.The C-index was 0.764,indicating relatively good consistency between the predicted and observed results.DTL and DLR have higher predictive value for 2-year PFS in nomogram.CONCLUSION Based on the multi-temporal characteristics of enhanced MRI and the constructed Nomograph,it provides a new strategy for predicting the PFS of transarterial chemoembolization treatment of HCC.

Oral fruquintinib combined with tegafur-gimeracil-oteracil potassium for advanced colorectal cancer to obtain longer progression-free survival:A case report

BACKGROUND After the failure of second-line standard therapy,effective treatment options for metastatic colorectal cancer are limited,and the duration of remission cannot meet clinical needs.In addition,associated drug toxicity may lead to treatment interruption that may affect patient outcomes.Therefore,more safe,effective and convenient treatments are urgently needed.CASE SUMMARY Here,we describe a patient with advanced colorectal cancer with multiple metastases in both lungs.Oxaliplatin combined with 5-fluorouracil or capecitabine was given as the first-line treatment,and bevacizumab combined with irinotecan was given as the second-line treatment after disease progression.However,treatment was interrupted due to recurrent grade 2 nausea and grade 1 diarrhea.He received targeted therapy with fruquintinib starting on August 26,2020 and responded well for 12 mo.After slow progression of the lung metastases,progression-free survival was again achieved over 13.5 mo by continued treatment of fruquintinib in combination with tegafur-gimeracil-oteracil potassium chemotherapy.Overall treatment duration was more than 25.5 mo.The treatments delayed tumor progression,reduced drug side effects,maintained a good quality of life,and further extended overall survival.CONCLUSION This case report detailed preliminary evidence showing that the combination of fruquintinib with tegafur-gimeracil-oteracil potassium chemotherapy double oral therapy may result in longer progression-free survival in patients with advanced colorectal cancer.

Impact of Real-Time Contrast-Enhanced Ultrasound-Guided Radiofrequency Ablation on Progression-Free Survival in Patients with Hepatocellular Carcinoma:a Retrospective Case-Control Study

Objective To compare the value of contrast-enhanced ultrasound(CEUS)and conventional ultrasound(US)during radiofrequency ablation(RFA)for the treatment of hepatocellular carcinoma(HCC)≥3.0 cm in diameter.Methods A total of 149 HCC patients treated with RFA guided by either CEUS or conventional US between January 2012 and June 2013 were retrospectively analyzed.Patients were divided into different groups based on the type of ultrasound guidance(CEUS or conventional US)and tumor volume(diameter<3.0 or≥3.0 cm).The progressionfree survival(PFS)and complete ablation rates were compared between groups,and risk factors for the PFS were investigated.Results Seventy four patients received CEUS-guided RFA,and conventional US was performed in 75 patients.Among patients with a tumor<3.0 cm,the PFS and complete ablation rates were similar.However,for patients with a tumor≥3.0 cm,those treated with CEUS had a significantly longer PFS(17.3 vs.3.1 months,HR=2.73;95%CI,1.28~5.81;P=0.007)and higher complete ablation rates at 6-and 12-month post-treatment(87.5%vs.57.7%,P=0.042;75.0%vs.38.5%,P=0.009,respectively)than those treated with conventional US-guided RFA.The type of treatment(P=0.024)and maximum tumour size(P=0.011)were both found to be independent factors associated with the PFS.Conclusion Compared with conventional US,CEUS is more effective for guiding RFA in patients with HCC≥3.0 cm.CEUS-guided RFA could target HCC more accurately,and its ability to immediately detect any residual tumor during RFA might contribute to an increase in complete ablation rates and reduced progression.

The impact of chemotherapy-naïve open radical cystectomy delay and perioperative transfusion on the recurrence-free survival: A perioperative parameters-based nomogram

Objective: To develop and internally validate a nomogram to predict recurrence-free survival (RFS) including the time to radical cystectomy (RC) and perioperative blood transfusion (PBT) as potential predictors.Methods: Patients who underwent open RC and ileal conduit between January 1996 to December 2016 were split into developing (n=948) and validating (n=237) cohorts. The time to radical cystectomy (TTC) was defined as the interval between the onset of symptoms and RC. The regression coefficients of the independent predictors obtained by Cox regression were used to construct the nomogram. Discrimination, validation, and clinical usefulness in the validation cohort were assessed by the area under the curve, the calibration plot, and decision curve analysis.Results: In the developing dataset, the 1-, 5-, and 10-year RFS were 83.0%, 47.2%, and 44.4%, respectively. On multivariate analysis, independent predictors were TTC (hazards ratio [HR] 1.07, 95% confidence interval [CI] 1.05-1.08, p<0.001), PBT (one unit: HR 1.40, 95% CI 1.03-1.90, p=0.03;two or more units: HR 1.72, 95% CI 1.29-2.29, p<0.001), bilateral hydronephrosis (HR 1.54, 95% CI 1.21-1.97, p<0.001), squamous cell carcinoma (HR 0.60, 95% CI 0.45-0.81, p=0.001), pT3-T4 (HR 1.77, 95% CI 1.41-2.22, p<0.001), lymph node status (HR 1.53, 95% CI 1.21-1.95, p<0.001), and lymphovascular invasion (HR 1.28, 95% CI 1.01-1.62, p=0.044). The areas under the curve in the validation dataset were 79.3%, 69.6%, and 76.2%, for 1-, 5-, and 10-year RFS, respectively. Calibration plots showed considerable correspondence between predicted and actual survival probabilities. The decision curve analysis revealed a better net benefit of the nomogram.Conclusion: A nomogram with good discrimination, validation, and clinical utility was constructed utilizing TTC and PBT in addition to standard pathological criteria.

Comparison of Semi-Parametric Shared Frailty Models for Bees’Survival

Survival analysis is a fundamental tool in medical science for time-to-event data. However, its application to colony organisms like bees poses challenges due to their social nature. Traditional survival models may not accurately capture the interdependence among individuals within a colony. Frailty models, accounting for shared risks within groups, offer a promising alternative. This study evaluates the performance of semi-parametric shared frailty models (gamma, inverse normal, and positive stable-in comparison to the traditional Cox model using bees’ survival data). We examined the effect of misspecification of the frailty distribution on regression and heterogeneity parameters using simulation and concluded that the heterogeneity parameter was more sensitive to misspecification of the frailty distribution and choice of initial parameters (cluster size and true heterogeneity parameter) compared to the regression parameter. From the data, parameter estimates for covariates were close for the four models but slightly higher for the Cox model. The shared gamma frailty model provided a better fit to the data in comparison with the other models. Therefore, when focusing on regression parameters, the gamma frailty model is recommended. This research underscores the importance of tailored survival methodologies for accurately analyzing time-to-event data in social organisms.

A radiomics prognostic scoring system for predicting progression-free survival in patients with stageⅣnon-small cell lung cancer treated with platinum-based chemotherapy

Objective:To develop and validate a radiomics prognostic scoring system(RPSS)for prediction of progressionfree survival(PFS)in patients with stageⅣnon-small cell lung cancer(NSCLC)treated with platinum-based chemotherapy.Methods:In this retrospective study,four independent cohorts of stageⅣNSCLC patients treated with platinum-based chemotherapy were included for model construction and validation(Discovery:n=159;Internal validation:n=156;External validation:n=81,Mutation validation:n=64).First,a total of 1,182 three-dimensional radiomics features were extracted from pre-treatment computed tomography(CT)images of each patient.Then,a radiomics signature was constructed using the least absolute shrinkage and selection operator method(LASSO)penalized Cox regression analysis.Finally,an individualized prognostic scoring system incorporating radiomics signature and clinicopathologic risk factors was proposed for PFS prediction.Results:The established radiomics signature consisting of 16 features showed good discrimination for classifying patients with high-risk and low-risk progression to chemotherapy in all cohorts(All P<0.05).On the multivariable analysis,independent factors for PFS were radiomics signature,performance status(PS),and N stage,which were all selected into construction of RPSS.The RPSS showed significant prognostic performance for predicting PFS in discovery[C-index:0.772,95%confidence interval(95%CI):0.765-0.779],internal validation(C-index:0.738,95%CI:0.730-0.746),external validation(C-index:0.750,95%CI:0.734-0.765),and mutation validation(Cindex:0.739,95%CI:0.720-0.758).Decision curve analysis revealed that RPSS significantly outperformed the clinicopathologic-based model in terms of clinical usefulness(All P<0.05).Conclusions:This study established a radiomics prognostic scoring system as RPSS that can be conveniently used to achieve individualized prediction of PFS probability for stageⅣNSCLC patients treated with platinumbased chemotherapy,which holds promise for guiding personalized pre-therapy of stageⅣNSCLC.

Somatic copy number alterations are predictive of progression-free survival in patients with lung adenocarcinoma undergoing radiotherapy

Objective:Lung cancer is the most common cause of cancer-related deaths worldwide.Somatic copy number alterations(SCNAs)have been used to predict responses to therapies in many cancers,including lung cancer.However,little is known about whether they are predictive of radiotherapy outcomes.We aimed to understand the prognostic value and biological functions of SCNAs.Methods:We analyzed the correlation between SCNAs and clinical outcomes in The Cancer Genome Atlas data for 486 patients with non-small cell lung cancer who received radiotherapy.Gene set enrichment analyses were performed to investigate the potential mechanisms underlying the roles of SCNAs in the radiotherapy response.Our results were validated in 20 patients with lung adenocarcinoma(LUAD)receiving radiotherapy.Results:SCNAs were a better predictor of progression-free survival(PFS)in LUAD(P=0.024)than in lung squamous carcinoma(P=0.18)in patients treated with radiotherapy.Univariate and multivariate regression analyses revealed the superiority of SCNAs in predicting PFS in patients with LUAD.Patients with stage I cancer and low SCNA levels had longer PFS than those with high SCNA levels(P=0.022).Our prognostic nomogram also showed that combining SCNAs and tumor/node/metastasis provided a better model for predicting long-term PFS.Additionally,high SCNA may activate the cell cycle pathway and induce tumorigenesis.Conclusions:SCNAs may be used to predict PFS in patients with early-stage LUAD with radiotherapy,in combination with TNM,with the aim of predicting long-term PFS.Therefore,SCNAs are a novel predictive biomarker for radiotherapy in patients with LUAD.

Progression-free survival as surrogate endpoint in advanced pancreatic cancer: meta-analysis of 30 randomized first-line trials

BACKGROUND：Progression-free survival（PFS）has not been extensively investigated as a surrogate for survival in the firstline treatments of pancreatic cancer.The aim of this review was to evaluate PFS as a potential surrogate endpoint for overall survival（OS）in advanced pancreatic cancer in trials comparing poly-chemotherapy to gemcitabine alone.DATA SOURCES： A systematic literature search in PubMed, Embase, Web of Science, and the Cochrane Central Register of Controlled Trials was conducted. The key words included randomized trial, first-line chemotherapy, pancreatic cancer, gemcitabine and poly-chemotherapy. Adjusted weighted linear regression was used to calculate Rs （Spearman＇s rank-order correlation coefficient） between PFS and post-progression survival （PPS） with OS （Rs） and between treatment effects on PFS and OS （RHR）. RESUEFS： A total of 30 trials including 8467 patients met the inclusion criteria. Correlation between the treatment effects on PFS and OS （RHR=0.78） and between the endpoint PFS and OS was high across all studies （Rs=0.75）. The slope of the re- gression line was 0.76±0.26, indicating that an agent produc- ing a 10% risk reduction for PFS will provide a 7.6%±2.6% risk reduction for OS. Correlation between PPS and OS was very strong （Rs=0.71） and accounted for more than 50% of the whole OS variability （R2=0.57）. CONCLUSION： Because of the robust correlation with OS and the potential influence of PPS caused by the second line therapies, it may be justified to consider PFS as a surrogate endpoint in trials evaluating new cytotoxic agents when gemcitabine is the control arm.

Post-radiation survival time in hepatocellular carcinoma based on predictors for CT-determined, transarterial embolization and various other parameters

AIM: In this retrospective study of unresectable hepatocellular carcinoma (HCC), we have investigated the efficacy of CT-derived parameters, laboratory measurements, clinical assessment and associated transarterial embolization (TAE) as predictors of post-radiotherapy survival time. METHODS: Sixty-six patients diagnosed with unresectable HCC that had undergone radiotherapy at two medical university hospitals in Taipei were enrolled in the study. Using multivariant analysis, pre-treatment parameters including tumor number and CT confirmation of PVT and ascites were compared. Multivariant analysis was also used for comparison of the mean pretreatment values for laboratory measurements, including alpha-fetoprotein, direct/total bilirubin and GOT/GPT levels, and clinical history of chronic hepatitis across the three survival-time categories. The x2 was used to test the significance of the relationship between survival time and TAE procedure. The P values for the above tests were deemed statistically significant where P<0.05. RESULTS: Portal vein thrombosis (P= 0.032) and ascites (P><0.05) were negative predictors of post-radiation survival time. Low-grade liver cirrhosis (A or B), lower tumor volume and low levels of AFT, GOT/GPT, and total bilirubin were predictors of longer post-radiation survival time (P<0.05). CONCLUSION: The CT and clinical and laboratory assessment provide a reference for, and enable estimation of, probable survival times in HCC patients after radiotherapy. Tumor volume, severity of liver cirrhosis, status with respect to portal vein thrombosis and ascites and AFT, GOT/GPT and total bilirubin values were significant predictors of survival in this study.

Is there an optimal time to initiate adjuvant chemotherapy to predict benefit of survival in non-small cell lung cancer?

Objective: Adjuvant chemotherapy (AC) after curative resection is known to improve the survival of patients with non-small cell lung cancer (NSCLC); however, few studies have reported the correlation between the time to initiation of AC (TTAC) and survival in NSCLC patients. Methods: The clinical data of 925 NSCLC patients who received curative resection and post-operative AC at the Cancer Hospital of Chinese Academy of Medical Sciences between 2003 and 2013 were retrospectively analyzed. TTAC was measured from the date of surgery to the initiation of AC. Disease-free survival (DFS) was defined as the duration from surgery to the time of tumor recurrence or last follow-up evaluation. The optimal cut-off value of TTAC was determined by maximally selected log-rank statistics. The DFS curve was estimated using the Kaplan-Meier method, and the Cox proportional hazards regression model was used to identify risk factors independently associated with DFS. Propensity score matching (PSM) was performed for survival analysis using the match data. Results: The optimal discriminating cut-off value of TTAC was set at d 35 after curative resection based on which the patients were assigned into two groups: group A (<= 35 d) and group B (> 35 d). There was no significant difference in the DFS between the two groups (P=0.246), indicating that the TTAC is not an independent prognostic factor for DFS. A further comparison continued to show no significant difference in the DFS among 258 PSM pairs (P=0.283). Conclusions: There was no significant correlation between the TTAC and DFS in NSCLC patients. Studies with larger samples are needed to further verify this conclusion.

The relationship between level of plasma D-dimer and survival time in metastatic gastric cancer patients

Objective:The principal purpose of this study was to determine the relationship between level of plasma D-dimer and survival time in metastatic gastric cancer patients.Methods:We retrospectively collected the data of plasma D-dimer in metastatic gastric cancer patients admitted in our Department (Department of Oncology,The Affiliated Changzheng Hospital,The Second Military Medical University,Shanghai,China) from October 2006 to October 2008 and analyzed the relationship between level of plasma D-dimer and survival time along with other clinicopathologic parameters.Results:A total of 82 patients were studied in our research,52 were males and 30 females,and the mean age was 57 years.The 48 cases had a normal plasma D-dimer level (<300μg/L) and 34 had a high plasma D-dimer level (≥300μg/L).In the normal and high plasma D-dimer level groups,the mean survival times were 10.9 (95% CI:9.8-12.2) months and 6.8(95% CI:4.4-7.6) months respectively,and the difference was statistically significant.Conclusion:Metastatic gastric cancer patients with high plasma D-dimer level had significantly shorter survival time than those with normal plasma D-dimer level.Level of plasma D-dimer can be referred as a potential predictor in metastatic gastric cancer patients.

Studies on the Relationship between Neuroendocrine Cellular Differentiation in Gastric Cancers and Post-operative Survival Time

OBJECTIVE To examine the ultrastructure of gastric cancer ceils by the electron microscope, in order to assess the relationship between neuroendocrine differentiation and post-operative survival time. METHODS NSE, Syn and CgA immunohistochemical labeling was conducted in 168 cases with a common-type of gastric cancer. Electron microscopy was performed in 80 cases with positive immunohistochemical labeling. These cases were followed-up for over 5 years and the post-operative survival data analyzed. RESULTS Neuroendocrine granules were found by electron microscopy in 39 cases. The rate of neuroendocrine differentiation found was 23% （39/168）, using routine diagnostic criteria and electron microscopy （REM）. The post-operative survival time of gastric cancer patients with neuroendocdne differentiation was significantly shorter （P=-0.0032） compared to those without neuroendocrine differentiation. CONCLUSION It is of significant clinical importance to determine if the neuroendocrine cells are differentiated in gastdc cancers. The gastric cancer patients with neuroendocrine differentiation have a shorter post-operative survival time and a poorer prognosis. Electron microscopy is a reliable method of providing a diagnosis.

Risk evaluation of splenic hilar lymph node metastasis and survival analysis of patients with advanced gastric cancer

Background:There is no consensus regarding the influence of prophylactic no.10 lymph node(LN)dissection in patients with advanced gastric cancer(AGC).We aimed to evaluate whether patients with AGC could benefit from no.10 LN dissection and to explore the clinicopathological indicators of no.10 LN metastasis.Methods:We analyzed the data of 218 patients with AGC who underwent standard D2 lymphadenectomy(SD2;n=108)or modified D2 lymphadenectomy(MD2;n=110)between January 2017 and January 2021.In addition,we examined factors influencing no.10 LN metastasis in the SD2 group.Results:Differentiation,tumor location,and no.4 positive LNs were significantly correlated with no.10 LN metastasis(P<0.05).Borrmann classification,differentiation,depth of invasion,LN metastasis(N),and tumor size were found to correlate with survival in univariate analyses.Age,sex,extent of gastrectomy,tumor location,and extent of lymphadenectomy were not associated with survival(P>0.05).The median survival times were 72.23 and 68.56months for the SD2 andMD2 groups,respectively(P=0.635).Postoperative major morbidity and mortality rates were 37.96%and 3.70%in the SD2 group,and 23.64%and 1.82%in the MD2 group,respectively.Conclusions:Based on our findings,prophylactic no.10 lymphadenectomy may be recommended in patients with AGC who exhibit positive no.4 LN status,poor differentiation,and tumors located on the greater curvature.

Bayesian Joint Modelling of Survival Time and Longitudinal CD4 Cell Counts Using Accelerated Failure Time and Generalized Error Distributions

Survival of HIV/AIDS patients is crucially dependent on comprehensive and targeted medical interventions such as supply of antiretroviral therapy and monitoring disease progression with CD4 T-cell counts. Statistical modelling approaches are helpful towards this goal. This study aims at developing Bayesian joint models with assumed generalized error distribution (GED) for the longitudinal CD4 data and two accelerated failure time distributions, Lognormal and loglogistic, for the survival time of HIV/AIDS patients. Data are obtained from patients under antiretroviral therapy follow-up at Shashemene referral hospital during January 2006-January 2012 and at Bale Robe general hospital during January 2008-March 2015. The Bayesian joint models are defined through latent variables and association parameters and with specified non-informative prior distributions for the model parameters. Simulations are conducted using Gibbs sampler algorithm implemented in the WinBUGS software. The results of the analyses of the two different data sets show that distributions of measurement errors of the longitudinal CD4 variable follow the generalized error distribution with fatter tails than the normal distribution. The Bayesian joint GED loglogistic models fit better to the data sets compared to the lognormal cases. Findings reveal that patients’ health can be improved over time. Compared to the males, female patients gain more CD4 counts. Survival time of a patient is negatively affected by TB infection. Moreover, increase in number of opportunistic infection implies decline of CD4 counts. Patients’ age negatively affects the disease marker with no effects on survival time. Improving weight may improve survival time of patients. Bayesian joint models with GED and AFT distributions are found to be useful in modelling the longitudinal and survival processes. Thus we recommend the generalized error distributions for measurement errors of the longitudinal data under the Bayesian joint modelling. Further studies may investigate the models with various types of shared random effects and more covariates with predictions.

A COMPARATIVE STUDY ON THERAPEUTIC RESPONSE AND SURVIVAL TIME OF PATIENTS WITH MULTIPLE MYELOMA TREATED WITH MODIFIED VMCP REGIMEN

Therapeutic response and survival time or 43 patients with multiple myeloma treated with modified VMCP(Vincristine,Melphalan, Cyelophosphamide and perdnisone;mVMCP)multidrug regimen are analyzed,and compared with those of 41 patients treated with VACP, M2, MP and other regimens.Therapeutic response to mVMCP regimen was better than that to other combination regimens(83. 5% VS 60.9%;P< 0.01).The median remission duration in patients responding to mVMCP was longer than that to other regimens(18.7 vs 12.2 mouths;P<0.001).But the survival time of two groups of responders was not signifficautly different(32. 5 vs 34.1 mouths; P>0.5).The prognostic significance of various pretreatment characteristics was evaluated in term of therapeutic response.The bone status and renal function had a significant inverse correlation with the survival time of patients responding to chemotherapy.Our data indicate that the patients with MM treated by mean or mVMCP regimen can obtain a better response in early treatment and maintain a longer remission duration as well as a better performance status. although the regimen can not prolong the patients survival time.

Lag time,high-risk histopathological features,metastasis,and survival interrelation in retinoblastoma:a perspective from lower-middle income country

AIM:To investigate the impact of lag time to metastasis and survival rates among patients with retinoblastoma.METHODS:This retrospective study was conducted with 52 patients from the Department of Ophthalmology and the Department of Pediatrics of Dr.Sardjito General Hospital,between 1^(st) January 2014 and 31^(st) December 2020.Lag time was defined as the time delay between the first sign of retinoblastoma to the diagnosis of retinoblastoma.The subjects with lag time>one year were included in the case group,while the subjects with lag time<one year were included in the control group.RESULTS:The lag time was significantly correlated with American Joint Committee on Cancer and Intraocular Classification of Retinoblastoma staging of retinoblastoma(P=0.005 and P=0.006,respectively).The lag time was also significantly correlated with both metastasis event[odds ratio(OR):5.06,95%Cl:1.56-16.44,P=0.006]and mortality(OR:4.54,95%Cl:1.37-15.07,P=0.011).The follow-up was continued for 32 subjects for 3y after initial diagnoses.Survival analysis revealed a significant difference among these two groups(P=0.021).Furthermore,lag time was significantly correlated with survival of retinoblastoma(r=-0.53,P=0.046).CONCLUSION:The study highlights the importance of lag time between the onset of first symptoms and the time of retinoblastoma diagnosis which significantly contribute to metastasis and mortality of patients with retinoblastoma.Examinations for the early detection of retinoblastoma should be performed for individuals at-risk to minimize lag time and improve the outcomes.

The Correlation of Lung Function Indexes and Survival Time of Patients with Advanced Lung Cancer

Background: To those patients with advanced lung cancer, the ultimate objective is to improve the quality of life, and lung function is an important factor affecting quality of life. We detect lung function of patients with lung cancer and study the correlation between lung function and the patients’ survival time, to provide reference for evaluation of disease progression and prognosis. Methods: Lung function was detected on 59 cases of lung cancer and 63 normal controls. The relationship between lung function indexes and survival time was analyzed. Results: There was significant difference in ventilation function and diffusing capacity between lung cancer group and control group. Vital capacity (VC), Forced expiratory volume in one second (FEV1), Forced vital capacity (FVC), peak expiratory flow (PEF), peak expiratory flow% (PEF%), Maximal ventilatory volume (MVV) were positively correlated to survival time in patients with advanced lung cancer (r = 0.28522064, 0.28053851, 0.28289252, 0.26908133, 0.26335034, 0.28409036, P 0.05), residual volume/total lung capacity was negatively correlated to survival time (r = ?0.30760097, P 0.05). Conclusions: The lung function decrease in the patients with lung cancer. Vital capacity (VC), Forced expiratory volume in one second (FEV1), Forced vital capacity (FVC), peak expiratory flow (PEF), peak expiratory flow% (PEF%), Maximal ventilatory volume (MVV), and residual volume/total lung capacity are correlated to survival time in patients with advanced lung cancer. The lung function indexes are important marker of prognosis of patients with lung cancer.

Predictive formulas expressing relationship between dose rate and survival time in total body irradiation in mice

The Gompertz model is the long-time well-known mathematical model of exponential expression among mortality models in the literature that are used to describe mortality and survival data of a population. The death rate of the “probacent” model developed by the author based on animal experiments, clinical applications and mathematical reasoning was applied to predict age-specific death rates in the US elderly population, 2001, and to express a relationship among dose rate, duration of exposure and mortality probability in total body irradiation in humans. The results of both studies revealed a remarkable agreement between “probacent”-formula-predicted and published-reported values of death rates in the US elderly population or mortality probabilities in total body irradiation in humans (p - value > 0.995 in χ2 test in each study). In this study, both the Gompertz and “probacent” models are applied to the Sacher’s comprehensive experimental data on survival times of mice daily exposed to various doses of total body irradiation until death occurs with an assumption that each of both models is applicable to the data. The purpose of this study is to construct general formulas expressing relationship between dose rate and survival time in total body irradiation in mice. In addition, it is attempted to test which model better fits the reported data. The results of the comparative study revealed that the “probacent” model not only fit the Sacher’s reported data but also remarkably better fit the reported data than the Gompertz model. The “probacent” model might be hopefully helpful in research in human tolerance to low dose rates for long durations of exposure in total body irradiation, and further in research in a variety of biomedical phenomena.

Application of a 2 Parameter Weibull Distribution in Modeling of State Holding Time in HIV/AIDS Transition Dynamics

This study investigates the application of the two-parameter Weibull distribution in modeling state holding times within HIV/AIDS progression dynamics. By comparing the performance of the Weibull-based Accelerated Failure Time (AFT) model, Cox Proportional Hazards model, and Survival model, we assess the effectiveness of these models in capturing survival rates across varying gender, age groups, and treatment categories. Simulated data was used to fit the models, with model identification criteria (AIC, BIC, and R2) applied for evaluation. Results indicate that the AFT model is particularly sensitive to interaction terms, showing significant effects for older age groups (50 - 60 years) and treatment interaction, while the Cox model provides a more stable fit across all age groups. The Survival model displayed variability, with its performance diminishing when interaction terms were introduced, particularly in older age groups. Overall, while the AFT model captures the complexities of interactions in the data, the Cox model’s stability suggests it may be better suited for general analyses without strong interaction effects. The findings highlight the importance of model selection in survival analysis, especially in complex disease progression scenarios like HIV/AIDS.

A Measure for Assessing Functions of Time-Varying Effects in Survival Analysis

A standard approach for analyses of survival data is the Cox proportional hazards model. It assumes that covariate effects are constant over time, i.e. that the hazards are proportional. With longer follow-up times, though, the effect of a variable often gets weaker and the proportional hazards (PH) assumption is violated. In the last years, several approaches have been proposed to detect and model such time-varying effects. However, comparison and evaluation of the various approaches is difficult. A suitable measure is needed that quantifies the difference between time-varying effects and enables judgement about which method is best, i.e. which estimate is closest to the true effect. In this paper we adapt a measure proposed for the area between smoothed curves of exposure to time-varying effects. This measure is based on the weighted area between curves of time-varying effects relative to the area under a reference function that represents the true effect. We introduce several weighting schemes and demonstrate the application and performance of this new measure in a real-life data set and a simulation study.