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Showing 4 results for Survival Analysis
Survival analysis of gastric cancer patients using Cox model: a five year study
Biglarian A, Hajizadeh E, Kazemnejad A, Zali M,
Volume 67, Issue 5 (8-2009)
Abstract

Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Background: Gastric cancer is the second most common cancer and known as the second cause of death due to cancers worldwide. Adenocarcinoma is the most fatal cancer in Iran and a patient with this kind of cancer, has a lower lifetime than others. In this research, the survival of patients with gastric carcinoma who were registered at Taleghani Hospital, were studied.
Methods:  291 patients with Gastric carcinoma who had received care, chemotherapy or chemoradiotherapy, at Taleghani Hospital in Tehran from 2002 to 2007 were studied as a historical cohort. Their survival rates and its relationship with 12 risk factors were assessed.
Results:  Of the 291 patients with Gastric carcinoma, 70.1 percent were men and others (29.9%) were women. The mean age of men was 62.26 years and of women was 59.32 years at the time of diagnosis. Most of patients (93.91%) were advanced stage and metastasis. The Cox proportional hazards model showed that age at diagnosis, tumor stage and histology type with survival time had significant relationships (p=0.039, p=0.042 and p=0.032 respectively).
Conclusion: The five-year survival rate and median lifetime of gastric cancer patients who underwent chemotherapy or chemoradiotherapy are very low and seems that one of the important reasons for this situation is delayed diagnosis. The scheme of public education about the early warning signs of the disease and diagnosis and administration of periodic examinations is unavoidable.


Stage-to-stage progression of chronic kidney disease in renal transplantation with chronic allograft dysfunction
Khalkhali H, Hajizadeh E, Kazemnezad A, Ghafari Moghadam A,
Volume 67, Issue 8 (11-2009)
Abstract

Normal 0 false false false EN-US X-NONE AR-SA MicrosoftInternetExplorer4 Background: Although the short-term results of kidney transplantation have improved greatly during the past decades, the long-term results have not improved according. Graft loss due to chronic allograft dysfunction (CAD) is a major concern in renal transplant recipients (RTRs). There is little data about disease progression in this patient population. In this paper, we investigated history of kidney function as the pattern, waiting time and rate of pass from intermediate stages in RTR with CAD.

Methods: In a single-center retrospective study, 214 RTRs with CAD investigated at the Urmia University Hospital urmia, Iran from 1997 to 2005. Kidney function at each visit assessed with GFR. We apply NKF and K/DOQI classification of chronic kidney disease (CKD) staging system to determine pattern of disease progression per stage in this group of patients.
Results: The pure death-censored graft loss was 26% with mean waiting time 81.7 months. 100% of RTRs passed from stage I to II in mean waiting time 26.3 months. The probability of prognostic factors transition from stage II to III was 88.9% with mean waiting time 25.5 months, transition from III to IV was 55.7% with mean waiting time of 24.9 months and transition for stage 4 to IV was 53.5% with mean waiting time of 18.2 months. In overall rate of transition from stage i to j in patients with stage III at the beginning of the study (time of start CAD's process) was faster than others.
Conclusions: This study revealed, that kidney function in first years after transplantation is one of the most important II to III of survival probability per stage and death-censored graft loss. Therefore care of RTRs in first year could potentially increase long-term kidney survival.


Factors affecting the antimonial treatment duration rate in patients with cutaneous leishmaniasis: survival analysis model
Amir Hamta, Abedin Saghafipour, Ehssan Mozaffari, Zahra Salemi ,
Volume 78, Issue 6 (9-2020)
Abstract
Background: Currently, cutaneous leishmaniasis (CL) as a parasitic disease is treated with Glucantime and Pentostam in most of the endemic countries. This study aimed to identify factors affecting the glucantime therapy duration rate in patients with CL using a survival analysis model.
Methods: This retrospective descriptive-analytic study was conducted on 1017 CL patients that were referred to the urban and rural comprehensive health centers of Qom Province under the supervision of Qom University of Medical Sciences, Qom, Iran, from April 2014 to March 2019 through the census. The recovery time was measured by the Kaplan-Meier method, and then the survival function was plotted based on each variable. The Log-Rank test was applied to analyze the differences among variables, and after the evaluation of the PH assumption by Shoenfeld residuals, a stepwise forward Cox progressive regression was used to determine factors affecting intralesional or systematic treatment duration in the patients involved with cutaneous leishmaniasis. 
Results: The recovery rate of lesions in cutaneous leishmaniasis cases was found to be 96.7% by the intralesional treatment and 93% by the systematic one. The mean recovery time for cutaneous leishmaniasis patients was 8.00 weeks for the intralesional treatment and 18.00 days for the systematic treatment. The only significant variable in the intralesional treatment was observed on cases with thigh lesions, meaning that those patients who had CL lesions on their thighs experienced a significant reduction in their recovery time. Furthermore, the lesion variable was also significant (P=0.039) as the recovery chance of those patients who had four or more CL lesions was 30% less.
Conclusion: The existence of lesions on CL patients’ thighs and a low number of lesions in CL patients can decrease the recovery time. The use of the Cox regression model in medical studies is more appropriate because not only does it consider the occurrence of the event but also it can reveal the occurrence time of the disease.

Survival Analysis of the Length of Hospital Stay of Suspected Stroke Patients Transferred by EMS to Ghaem Hospital in Mashhad
Razieh Yousefi , Payam Sasannejad, Eisa Nazar, Ali Hadianfar, Mohammad Taghi Shakeri., Zahra Jafari ,
Volume 81, Issue 11 (2-2024)
Abstract
Background: Identifying factors that influence the length of hospital stay for suspected stroke patients is crucial for optimizing the utilization of hospital resources. This study aimed to determine the factors associated with the length of hospital stay for suspected stroke patients transferred to Qaem Hospital in Mashhad through emergency services using survival analysis.
Methods: In this historical cohort study, general information was gathered for all suspected stroke patients who sought emergency services in Mashhad, the largest city in northeast Iran, from March 21, 2018, to March 20, 2019, and were then transferred to the Emergency Department of Qaem Hospital. Pre-hospital emergency data were integrated with hospital records using the mission ID. The primary outcome assessed in the study was the length of hospital stay, with model implementation carried out using the statistical software Stata.
Results: The median hospitalization time until patients' recovery was  seven days. Out of the 578 participants, 386 cases (66.8%) recovered, while the remaining 190 cases (33.2%) were censored (83 individuals had died during the study, and 107 individuals had exited the hospital for other reasons). The average age of patients at the time of hospitalization was 71.13±13.01 years. Statistical analysis employing Log-rank and Breslow tests identified a significant difference in hospitalization duration among patients receiving various levels of care and based on their insurance status. During multivariate analysis, the Cox regression model was considered unsuitable due to some variables not meeting the proportional hazards assumption, leading to the utilization of AFT models. Following the evaluation of AFT models, including Log-normal, Log-logistic, Exponential, and Weibull, the log-normal model emerged as the most suitable choice, exhibiting AIC and BIC values of 1273.909 and 1356.740, respectively. Significant variables influencing length of stay included patient admission priority, insurance status, season, and residency status.
Conclusion: The study suggests that parametric survival models are effective for analyzing lifetime data. Additionally, in light of the significant variables identified, enhancing facility readiness and resource allocation could facilitate more efficient planning and implementation.

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