Estimation Of Mean Survival Time Research Articles

Survival analysis for estimating lamb survival up to weaning in Harnali sheep

The present study was carried out to estimate lamb survival (in days) from birth to weaning under survival analysis using data records from 2057 Harnali lambs born to 134 sires and 623 dams between the period from 2001 to 2020. The weaning age in resourced population was 90 days from birth. The hazard ratio in terms of risk of death up to weaning was determined using Cox proportional hazards model by subjecting some fixed factors such as year of birth, sex of lamb, birth weight (kg), dam's weight at lambing (kg) and dam's age at lambing (years). The overall survivability up to weaning among lambs was 91.59% and Kaplan-Meier estimates of mean survival time up to weaning was 85.77 days. Cox proportional hazard modelling revealed that the hazards of death up to weaning was higher in male lambs [1.66, 95% confidence interval (CI): 1.22-2.26] compared with female lambs [hazard ratio (HR) = 1.00]. It was also observed that the hazards of death (HR = 0.91, 95% CI: 0.88-0.94) had decreasing trends over years. For birth weight (kg), hazard rate was 0.34 (95% CI: 0.25-0.46), which indicated that the risk of pre-weaning mortality was lower as birth weight increases. The weight and age of dams at lambing did not influence the survival time of studied population. The present findings indicated that survival time increased in studied lambs over the years and it could be increased more by giving more emphasis on better litter weight and general health aspects at farm level.

Evaluating center‐specific long‐term outcomes through differences in mean survival time: Analysis of national kidney transplant data

Center-specific survival outcomes of kidney transplant recipients are an important quality measure, with several challenges. Existing methods based on restricted mean lifetime tend to focus on short- and medium-term clinical outcomes and may fail to capture long-term effects associated with quality of follow-up care. In this report, we propose methods that combine a lognormal frailty model and piecewise exponential baseline rates to compare the mean survival time across centers. The proposed methods allow for the consistent estimation of mean survival time as opposed to restricted mean lifetime and, within this context, permits more accurate profiling of long-term center-specific outcomes. Asymptotic properties of the proposed estimators are derived, and finite-sample properties are examined through simulation. The proposed methods are then applied to national kidney transplant data. The novelty of the proposed techniques arises from several angles. We utilize mean survival, in contrast to the most previous works that considered the restricted mean. Few previous studies have used the integrated survival function as a basis for center effects. Few provider profiling methods use a random effects model to estimate fixed center effects.

Predicting Mean Survival Time from Reported Median Survival Time for Cancer Patients.

Mean duration of survival following treatment is a prerequisite for cost-effectiveness analyses used for assessing new and costly life-extending therapies for cancer patients. Mean survival time is rarely reported due to censoring imposed by limited follow-up time, whereas the median survival time often is. The empirical relationship between mean and median survival time for cancer patients is not known. To derive the empirical associations between mean and median survival time across cancer types and to validate this empirical prediction approach and compare it with the standard approach of fitting a Weibull distribution. We included all patients in Norway diagnosed from 1960 to 1999 with one of the 13 most common solid tumor cancers until emigration, death, or 31 December 2011, whichever came first. Observed median, restricted mean, and mean survival times were obtained in subcohorts defined by patients' sex, age, cancer type, and time period of diagnosis, which had nearly complete follow-up. Based on theoretical considerations, we fitted a linear relationship between observed means and medians on the log scale. For validation, we estimated mean survival from medians of bootstrap samples with artificially induced censoring and compared with fitting a Weibull distribution. A linear relationship between log-mean survival time and log-median survival time was identified for the 6 cancers with shortest survival plus metastasized breast and prostate cancers. The predicted means of the empirical approach had smaller bias than the standard Weibull approach. For cancer diagnoses with poor prognosis, mean survival times could be predicted from corresponding medians. This empirical prediction approach is useful for validation of estimates of mean survival time and sensitivity analyses in settings with aggregated data only.

Colorectal Cancer Surgery in Portal Hypertensive Patients

Oxaliplatin is used in adjuvant treatment of colorectal cancer and is associated with sinusoidal obstruction syndrome. Few data are available on its effects in patients in whom portal hypertension was diagnosed before cancer treatment. Our aim was to investigate short- and long-term outcomes of surgery for colorectal cancer in patients with portal hypertension with or without cirrhosis, particularly regarding effects of adjuvant chemotherapy with oxaliplatin. This was a prospective cohort study performed at an academic medical center. Patients with stage II or III colorectal cancer and portal hypertension who underwent curative resection were included. All patients received adjuvant chemotherapy with oxaliplatin (FOLFOX 4) or 5-fluorouracil and leucovorin. Potential predictive laboratory and clinical variables and postoperative (30-day) and long-term morbidity and mortality were recorded. Of 63 patients enrolled, 23 (37%) had a total of 82 postoperative complications; 5 patients (8%) died within 30 days postoperatively. Univariate analysis showed that severe portal hypertension, preoperative Child class B, low albumin, the presence of ascites, preoperative upper GI tract bleeding, and high intraoperative blood loss were linked to postoperative morbidity. Presence of postoperative infection (p = 0.004), presence of preoperative ascites (p = 0.01), high intraoperative blood loss (p = 0.02), and preoperative upper GI tract bleeding (p = 0.03) were significantly related to mortality. Of 58 patients receiving adjuvant chemotherapy, 20 received the oxaliplatin regimen and 38 received 5-fluorouracil/leucovorin without oxaliplatin. The median length of follow-up was 26 (range, 6-36) months. Kaplan-Meier analyses showed that patients who received oxaliplatin had higher cumulative incidences of newly developed esophageal varices (p = 0.002), GI tract bleeding (p = 0.02), and newly formed ascites (p = 0.03). Death occurred in 8 of 20 patients (40%) in the oxaliplatin group and in 5 of 38 patients (13%) in the 5-fluorouracil group. Kaplan-Meier estimates of mean survival time were 34.4 months (95% CI, 32.4-36.5) in the 5-fluorouracil/leucovorin group vs 29.9 months (95% CI, 26-33.7) in the oxaliplatin group, and patients receiving oxaliplatin had a significantly higher relative risk of death (HR = 2.98; 95% CI, 1.03-8.65). Cancer-specific mortality was not related to treatment type. The study was limited by the relatively small sample size and lack of randomization, which may have led to selection bias in treatment regimens. Colorectal cancer surgery can be done safely in portal hypertensive patients with good hepatic function; however, higher mortality is expected in patients with compromised hepatic function reserve. Compared with adjuvant chemotherapy without oxaliplatin, oxaliplatin-based chemotherapy does not significantly reduce cancer-specific mortality and may increase overall morbidity and mortality. Therefore, oxaliplatin-based chemotherapy should be used with caution in patients who have portal hypertension, even in those with good liver function.

Evaluating Joint Effects of Induction–Salvage Treatment Regimes on Overall Survival in Acute Leukaemia

Typical oncology practice often includes not only an initial, frontline treatment, but also subsequent treatments given if the initial treatment fails. The physician chooses a treatment at each stage based on the patient's baseline covariates and history of previous treatments and outcomes. Such sequentially adaptive medical decision-making processes are known as dynamic treatment regimes, treatment policies, or multi-stage adaptive treatment strategies. Conventional analyses in terms of frontline treatments that ignore subsequent treatments may be misleading, because they actually are an evaluation of more than front-line treatment effects on outcome. We are motivated by data from a randomized trial of four combination chemotherapies given as frontline treatments to patients with acute leukemia. Most patients in the trial also received a second-line treatment, chosen adaptively and subjectively rather than by randomization, either because the initial treatment was ineffective or the patient's cancer later recurred. We evaluate effects on overall survival time of the 16 two-stage strategies that actually were used. Our methods include a likelihood-based regression approach in which the transition times of all possible multi-stage outcome paths are modeled, and estimating equations with inverse probability of treatment weighting to correct for bias. While the two approaches give different numerical estimates of mean survival time, they lead to the same substantive conclusions when comparing the two-stage regimes.

Generalized age-dependent model for estimation of mean survival time in the presence of two competing risks

Abstract The paper is motivated towards developing a generalized probability model describing the longevity of a system exposed to paired risks R1 and R2 which are dependent. The bivariate exponential model of Freund (1961) with failure times X and Y under risks R1 and R2 with a time-independent hazard rate set-up has been generalized by incorporating an additional age factor, t, as a variable. The hazard rates due to R1 and R2 have been changed from a to α(t) = αtα−1, and from β to β(f) = βtβ−1 where α,β > 0 which are Weibull hazard functions for α,β > 1. Further conditions are imposed such that α is changed to α' when R2 is off and β is changed to β' when R1 is off. The trivariate distribution of Freund so generalized has again been doubly truncated in the range a  t  b, for a, b > 0; and the conditional distribution of X and Y given t has been used to study the role of the component's age in the context of the system's survival under paired dependent risks in the finite age range.