Retrospective cohort study on the postoperative survival rate enhancement of patients with colorectal cancer using three traditional Chinese medicine formulations:evidence from 1,361 cases

Background:Prior studies have affirmed the safety and effectiveness of traditional Chinese medicine in treating colorectal cancer patients.However,definitive evidence regarding whether traditional Chinese medicine can significantly enhance the survival of colorectal cancer patients remains elusive.This study seeks to provide conclusive insights by examining the postoperative administration of Xihuang capsules,Pingxiao capsules,and Zilongjin tablets and its impact on the 5-year overall survival(OS)and disease-free survival(DFS)rates among colorectal cancer patients.Methods:A retrospective study was conducted,involving 1,361 patients selected from the medical center.This retrospective study was carried out at a medical center in Tianjin,China.We assessed differences in postoperative OS and DFS between the control group and the medication group using Kaplan–Meier survival analysis and Cox proportional hazards modeling.Additionally,propensity score matching was used to mitigate imbalances in baseline characteristics among patients.Results:Before propensity score matching,Xihuang capsules could prolong the 5-year OS(79.9%vs.81.4%,P=0.0480)and 5-year DFS(74.9%vs.79.5%,P=0.0046)of patients after surgery.Similar conclusions were obtained after propensity score matching:OS(74.8%vs.78.3%,P=0.0084),DFS(72.7%vs.78.9%,P=0.008).Patients taking Pingxiao capsules showed improved 5-year OS(77.2%vs.84.0%,P=0.0383)and 5-year DFS(69.9%vs.80.0%,P=0.0157)after propensity score matching.Patients taking Zilongjin tablets showed improvement in the 2-year OS(84.2%vs.93.1%,P=0.0390)and 1-year DFS(88.2%vs.92.0%,P=0.0320)after propensity score matching.Conclusion:Xihuang capsules and Pingxiao capsules significantly improved the 5-year OS and DFS of patients with colorectal cancer after surgery.Zilongjin tablets showed improvement in the 2-year OS and 1-year DFS after surgery for patients.

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.

The effect of long-term traditional Chinese medicine treatment on disease-free survival of postoperative stage I-III lung cancer patients:a retrospective cohort study

Objective:Traditional Chinese medicine(TCM)has been extensively used as one of popular alternative therapies for several cancers.However,it remains unclear whether TCM treatment is associated with longer survival in lung cancer patients.In this study,we explored the effect of long-term TCM treatment on patients with different stages of lung cancer.Methods:All information of lung cancer patients with stage I-III disease from January 2007 to September 2015 was collected for this retrospective cohort study.Those who were treated with TCM after surgery were divided into TCM group and the others were into the non-TCM group(control group).All patients were regularly followed up by clinic appointment or phone,and all survival data were collected from databases after the last follow-up in October 2017.Results:A total of 575 patients were included in this study,with 299 patients in the TCM group and 276 in the control group.For all patients,5-year disease-free survival(DFS)was 62.2% in TCM group and 42.1% in the control group,and 6-year DFSs were 51.8% and 35.4%,respectively(HR=0.51,95% CI:0.40 to 0.66,log-rank P≤0.001).For patients with stage I,5-year DFSs were 83.7%(TCM group)and 57.5%(control group)and 6-year DFSs were 73.7% and 51.9%,respectively(HR=0.30,95% CI:0.18 to 0.50,log-rank P≤0.001).For patients with stage II in the TCM group and the control group,5-year DFSs were 59.4% and 17.6% and 6-year DFSs were 44.7% and 17.6%,respectively(HR=0.31,95% CI:0.19 to 0.52,log-rank P≤0.001),and for patients with stage III,5-year and 6-year DFSs in the TCM group were 18.7% and 12.5% compared with 28.4% and 20.3% in the control group(HR=1.06,95% CI:0.72 to 1.56,log-rank P=0.76).Conclusions:This study demonstrated that long-term TCM treatment as an adjuvant therapy is able to improve the DFS of postoperative stage I-III lung cancer patients,especially in patients with stage I and II disease.However,these observational findings need being validated by large sample randomized controlled trials.

Prognostic factors for disease-free survival in postoperative patients with hepatocellular carcinoma and construction of a nomogram model

BACKGROUND Hepatocellular carcinoma(HCC)is the most common type of liver cancer and has a high risk of invasion and metastasis along with a poor prognosis.AIM To investigate the independent predictive markers for disease-free survival(DFS)in patients with HCC and establish a trustworthy nomogram.METHODS In this study,445 patients who were hospitalized in The First Affiliated Hospital of Anhui Medical College between December 2009 and December 2014 were retrospectively examined.The survival curve was plotted using the Kaplan–Meier method and survival was determined using the log-rank test.To identify the prognostic variables,multivariate Cox regression analyses were carried out.To predict the DFS in patients with HCC,a nomogram was created.C-indices and receiver operator characteristic curves were used to evaluate the nomogram’s performance.Decision curve analysis(DCA)was used to evaluate the clinical application value of the nomogram.RESULTS Longer DFS was observed in patients with the following characteristics:elderly,I–II stage,and no history of hepatitis B.The calibration curve showed that this nomogram was reliable and had a higher area under the curve value than the tumor node metastasis(TNM)stage.Moreover,the DCA curve revealed that the nomogram had good clinical applicability in predicting 3-and 5-year DFS in HCC patients after surgery.CONCLUSION Age,TNM stage,and history of hepatitis B infection were independent factors for DFS in HCC patients,and a novel nomogram for DFS of HCC patients was created and validated.

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.

Deep learning-based multi-modal data integration enhancing breast cancer disease-free survival prediction

Background:The prognosis of breast cancer is often unfavorable,emphasizing the need for early metastasis risk detection and accurate treatment predictions.This study aimed to develop a novel multi-modal deep learning model using preoperative data to predict disease-free survival(DFS).Methods:We retrospectively collected pathology imaging,molecular and clinical data from The Cancer Genome Atlas and one independent institution in China.We developed a novel Deep Learning Clinical Medicine Based Pathological Gene Multi-modal(DeepClinMed-PGM)model for DFS prediction,integrating clinicopathological data with molecular insights.The patients included the training cohort(n=741),internal validation cohort(n=184),and external testing cohort(n=95).Result:Integrating multi-modal data into the DeepClinMed-PGM model significantly improved area under the receiver operating characteristic curve(AUC)values.In the training cohort,AUC values for 1-,3-,and 5-year DFS predictions increased to 0.979,0.957,and 0.871,while in the external testing cohort,the values reached 0.851,0.878,and 0.938 for 1-,2-,and 3-year DFS predictions,respectively.The DeepClinMed-PGM's robust discriminative capabilities were consistently evident across various cohorts,including the training cohort[hazard ratio(HR)0.027,95%confidence interval(CI)0.0016-0.046,P<0.0001],the internal validation cohort(HR 0.117,95%CI 0.041-0.334,P<0.0001),and the external cohort(HR 0.061,95%CI 0.017-0.218,P<0.0001).Additionally,the DeepClinMed-PGM model demonstrated C-index values of 0.925,0.823,and 0.864 within the three cohorts,respectively.Conclusion:This study introduces an approach to breast cancer prognosis,integrating imaging and molecular and clinical data for enhanced predictive accuracy,offering promise for personalized treatment strategies.

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.

A Comparison of Within-Subjects and Between-Subjects Designs in Studies with Discrete-Time Survival Outcomes

Crossover designs are well-known to have major advantages when comparing the effects of various non-curative treatments. We compare efficiencies of several crossover designs along with the Balaam’s design with that of a parallel group design pertaining to longitudinal studies where event time can only be measured in discrete time intervals. With equally sized sequences, the parallel group design results in the greater efficiency if the number of time periods is small. However, the crossover and Balaam’s designs tend to be more efficient as the study duration increases. The degree to which these designs add efficiency depends on the baseline hazard function and effect size. Additionally, we incorporate different cost considerations at the subject level when comparing the designs to determine the most cost-efficient design. Researchers might consider the crossover or Balaam’s design more efficient if the duration of the study is long enough, especially if the costs of applying the baseline treatment are higher.

High level of preoperative carbohydrate antigen 19-9 is a poor survival predictor in gastric cancer

AIM:To assess the clinical significance and the prognostic value of preoperative serum carbohydrate antigen 19-9(CA 19-9)level in gastric cancer.METHODS:Between January 2005 and December2006,1960 patients underwent surgery for histologically confirmed gastric cancer.Of these,163 patients had elevated serum levels of CA 19-9 preoperatively,and1628 patients had normal serum levels of CA 19-9 preoperatively.For this study,325 patients were selected from the group of 1628 patients by age,sex,and cancer stage to serve as controls.Statistically significant differences in survival rates were calculated using the log-rank test.A P value less than 0.05 was considered statistically significant and was determined using SAS software.RESULTS:The baseline characteristics showed some differences between the two groups with regard to histology.Overall survival(OS)in the elevated and nonelevated group was 37.90 and 68.67 mo,respectively(P<0.001).N stage(P=0.001)was a significant predictor of disease-free survival by multivariate analysis.Also,N stage(P<0.001),and the presence of peritoneal metastasis(P<0.001)remained independent factors in predicting OS by multivariate analysis.Additionally,preoperative serum CA 19-9 levels were significantly associated with OS in univariate(P=0.009)and multivariate(P=0.021)analyses.CONCLUSION:Serum CA 19-9 can be considered an independent prognostic factor in predicting OS in patients anticipating surgery for gastric cancer.