Determining Prognostic Factors of Disease-Free Survival in Breast Cancer Using Censored Quantile Regression

Background

The analysis of disease-free survival and related factors leads to a better understanding of the patient's condition and recurrence-related characteristics and provides a basis for more appropriate treatment guidance. In this study, we aimed to investigate the role of prognostic factors on disease-free survival in breast cancer with a quantile regression model.

Methods

This retrospective study was conducted by reviewing data obtained from 2056 breast cancer patients. Age at diagnosis and education status, tumor size, lymph node ratio, tumor grade, estrogen receptor and progesterone receptor, type of surgery, use of radiotherapy, chemotherapy, and hormone therapy were the prognosis factors considered in this study. A quantile regression model was used to investigate prognostic factors of disease-free survival in breast cancer.

Results

Disease recurrence was verified in 251 (13.9%) women, and 39 (0.02%) women died before experience recurrence. The 10th percentile of disease-free survival for patients with the hormone therapy was 23.85 months greater than patients who did not receive this treatment (P value < .001). In the examination of the tumor size, the 10th and 20th percentiles of disease-free survival for patients with tumor size > 5 cm were 31.06 and 27 months less than patients with the tumor size < 2 cm, respectively (P value = .006 and .021, respectively). Compared with grade 1 tumors, the 10th and 20th percentiles of disease-free survival for patients with grade 3 tumors decreased 30.11 and 38.32 months, respectively (P value < .001 and .038, respectively). The 10th and 20th percentiles of disease-free survival decreased 28.16 and 45.32 months with a 1 unit increase in lymph node ratio, respectively (P value = .032 and .032, respectively).

Conclusions

Among the prognostic factors, tumor size, grade, and lymph node ratio showed a close relationship with disease-free survival in breast cancer. The findings indicated that developing public screening and educational programs through the health care system with more emphasis on low-educated women is needed among Iranian women.

Association of life satisfaction with disability-free survival: role of chronic diseases and healthy lifestyle

BACKGROUND

this article investigates the association between life satisfaction and disability-free survival, and explores the roles of chronic diseases and healthy lifestyle in this association.

METHOD

a cohort of 2,116 functionally independent adults aged ≥60 was followed up to 12 years. At baseline, life satisfaction was assessed with the Life Satisfaction Index A (LSI-A). Disability-free survival was defined as the survival till the first occurrence of either death, dementia or physical disability. Information on lifestyle factors was collected via questionnaire. Chronic diseases were ascertained through clinical examinations at baseline and each follow-up. Data were analysed using Cox proportional hazard regression models and Laplace regression.

RESULTS

over follow-up, 1,121 participants died, developed dementia, or became disabled. High LSI-A versus Low LSI-A had a lower risk of death, dementia and physical disability (hazard ratio [HR] 0.79, 95% confidence intervals [CI] 0.67-0.94), and had a longer disability-free period by 1.73 (95% CI 0.18-3.32) years. In mediation analysis, accumulation of chronic diseases mediated 17.8% of the association between LSI-A and disability-free survival. In joint effect analysis, participants with high LSI-A and a favourable lifestyle profile had a HR of 0.53 (95% CI 0.41-0.69) for the composite endpoint, and lived 3.2 (95% CI 1.35-5.11) disability-free years longer than those with low life satisfaction and an unfavourable lifestyle profile.

DISCUSSION

high life satisfaction is independently associated with longer disability-free survival. This association is partially mediated by a lower burden of chronic diseases and is reinforced by healthy lifestyle.

Survival Percentile and Predictors of Difference in Survival among Hemodialysis Patients and Their Additive Interaction Using Laplace Regression

Background: Identifying survival modifiable factors and additive interaction between them could help in prioritizing the clinical care of Hemodialysis (HD) patients. We aimed to examine the survival rate and its predictors in HD patients; and explore the additive interaction between survival modifiable factors.

Study design: A retrospective cohort study.

Methods: The present study was performed on 1142 HD patients in Hamadan Province, western Iran from 2007 to 2017. Data were collected through a researcher-made checklist on hospital records. Laplace regression was used to evaluate differences in 40^th survival percentiles in different levels of predictors as well as exploring the pairwise additive interactions between variables.

Results: We observed significantly higher survival in nonsmoker patients (40^th percentile difference = 5.34 months, 95% CI: 2.06, 8.61). Survival was shorter by more than 3 years in CRP positive patients (40^th percentile difference=36.9 months, 95% CI: 32.37, 41.42). Patients with normal albumin (40^th percentile difference =24.92, 95% CI: 18.04, 31.80) and hemoglobin (40^th percentile difference = 18.65, 95% CI: 12.43, 24.86) had significantly higher survival (P<0.001). There was super-additive interaction between being CRP negative and nonsmoker (β₃ = 9.42 months, 95% CI: 3.35, 15.49 (P=0.002)).

Conclusion: High CRP and low serum albumin and hemoglobin were associated with the increased risk of death in HD patients. The results of this study support the presence of super-additive interaction between CRP status with serum hemoglobin and also CRP status with smoking, resulting in excess survival in HD patients.

The Japanese Dietary Pattern Is Associated with Longer Disability-Free Survival Time in the General Elderly Population in the Ohsaki Cohort 2006 Study

BACKGROUND

Epidemiologic observations have raised expectations that the Japanese dietary pattern could promote longer disability-free survival (DFS) times among the Japanese population; however, no previous study has examined this issue.

OBJECTIVE

The aim of this study was to investigate the association between the Japanese dietary pattern and DFS time in the elderly Japanese population.

METHODS

We analyzed follow-up data covering a 10-y period for 9456 elderly Japanese individuals (aged ≥65 y) participating in a community-based prospective cohort study. Dietary habits were assessed using a food-frequency questionnaire. Based on previous studies, we used 9 food items to calculate the Japanese Diet Index (JDI) score: rice, miso soup, fish and shellfish, green and yellow vegetables, seaweed, pickled vegetables, green tea (1 point for each item if the consumption value was more than or equal to the median, and 0 points otherwise), beef and pork, and coffee (0 points for each item if the consumption value was more than or equal to the median, and 1 point otherwise). Differences in median age at incident disability or death [50th percentile differences (PDs)] according to quartiles (Q1-Q4) of the JDI score were estimated using Laplace regression.

RESULTS

During the follow-up period, 4233 (44.8%) incident disability or death events occurred. In addition, a higher JDI score was significantly associated with longer DFS time: compared with the lowest quartile of JDI scores (Q1), the multivariate-adjusted 50th PD (95% CI) was 7.1 (1.8, 12.4) mo longer for Q4. Each 1-SD increase of the JDI score was associated with 3.7 (1.7, 5.7) additional months of life without disability (P-trend < 0.01). No differences were seen in sex or chronic condition (no or ≥1 chronic condition) at baseline. A post hoc analysis showed a larger effect on DFS time when using a modified JDI score without coffee.

CONCLUSION

These results suggest that the Japanese dietary pattern is associated with improved DFS time in the general elderly population.

Social and Behavioural Determinants of the Difference in Survival among Older Adults in Japan and England

BACKGROUND

A rapidly ageing population presents major challenges to health and social care services. Cross-country comparative studies on survival among older adults are limited. In addition, Japan, the country with the longest life expectancy, is rarely included in these cross-country comparisons.

OBJECTIVE

We examined the relative contributions of social and behavioural factors on the differences in survival among older people in Japan and England.

METHODS

We used data from the Japan Gerontological Evaluation Study (JAGES; n = 13,176) and the English Longitudinal Study of Ageing (ELSA; n = 5,551) to analyse all-cause mortality up to 9.4 years from the baseline. Applying Laplace regression models, the 15th survival percentile difference was estimated.

RESULTS

During the follow-up, 31.3% of women and 38.6% of men in the ELSA died, whereas 19.3% of women and 31.3% of men in the JAGES died. After adjusting for age and baseline health status, JAGES participants had longer survival than ELSA participants by 318.8 days for women and by 131.6 days for men. Family-based social relationships contributed to 105.4 days longer survival in JAGES than ELSA men. Fewer friendship-based social relationships shortened the JAGES men's survival by 45.4 days compared to ELSA men. Currently not being a smoker contributed to longer survival for JAGES women (197.7 days) and ELSA men (46.6 days), and having lower BMI reduced the survival of JAGES participants by 129.0 days for women and by 212.2 days for men.

CONCLUSION

Compared to participants in England, Japanese older people lived longer mainly because of non-smoking for women and family-based social relationships for men. In contrast, a lower rate of underweight, men's better friendship-based social relationships, and a lower smoking rate contributed to survival among participants in England.

Using Laplace Regression to Model and Predict Percentiles of Age at Death When Age Is the Primary Time Scale

Increasingly often in epidemiologic research, associations between survival time and predictors of interest are measured by differences between distribution functions rather than hazard functions. For example, differences in percentiles of survival time, expressed in absolute time units (e.g., weeks), may complement the popular risk ratios, which are unitless measures. When analyzing time to an event of interest (e.g., death) in prospective cohort studies, the time scale can be set to start at birth or at study entry. The advantages of one time origin over the other have been thoroughly explored for the estimation of risks but not for the estimation of survival percentiles. In this paper, we analyze the use of different time scales in the estimation of survival percentiles with Laplace regression. Using this regression method, investigators can estimate percentiles of survival time over levels of an exposure of interest while adjusting for potential confounders. Our findings may help to improve modeling strategies and ease interpretation in the estimation of survival percentiles in prospective cohort studies.

High levels of soluble tumor necrosis factor receptors 1 and 2 and their association with mortality in patients undergoing hemodialysis

OBJECTIVE

Circulating soluble tumor necrosis factor receptors 1 and 2 (sTNFR1 and sTNFR2) are associated with chronic kidney disease (CKD) progression in patients with CKD or diabetes, and with higher mortality. However, data in patients with end-stage renal disease are scarce. Therefore, we analyzed serum levels of sTNFR1 and sTNFR2 and investigated their association with inflammatory markers and mortality in dialysis patients.

RESEARCH DESIGN AND METHODS

This was a longitudinal cohort study of 207 prevalent patients (median age 66 years, 56% men) undergoing hemodialysis in Stockholm, Sweden. Demographics, clinical characteristics, including comorbidities and laboratory data, were obtained at baseline, together with prospective follow-up for mortality.

RESULTS

The median sTNFR1 and sTNFR2 levels were 17,680 ng/l [95% confidence interval (CI) 17,023-18,337] and 24,450 ng/l (95% CI 23,721-25,179), respectively. During a follow-up of 31 months (interquartile range, 21-38), 77 patients died. There was no association between the levels of sTNFRs and mortality in Cox regression models, and no consistent trend towards higher or lower mortality was seen in Laplace regression models. sTNFR1 and sTNFR2 levels were highly associated with other inflammatory markers including interleukin-6, pentraxin 3 and TNF-α.

CONCLUSIONS

Prevalent hemodialysis patients have several-fold higher levels of sTNFRs compared to previous studies in CKD stage 4 patients. As no consistent association between TNFR and mortality was observed, clinical implications of measuring these receptors to predict outcome end-stage renal disease patients provide limited results.

Sleep duration and survival percentiles across categories of physical activity

The association between long sleep duration and death is not fully understood. Long sleep is associated with low physical activity, which is a strong predictor of death. Our aim was to investigate the association between sleep duration and death across categories of total physical activity in a large prospective cohort of Swedish men and women. We followed a population-based cohort of 70,973 participants (37,846 men and 33,127 women), aged 45-83 years, from January 1998 to December 2012. Sleep duration and physical activity levels were assessed through a questionnaire. We evaluated the association of interest in terms of mortality rates by estimating hazard ratios with Cox regression and in terms of survival by evaluating 15th survival percentile differences with Laplace regression. During 15 years of follow-up, we recorded 14,575 deaths (8,436 men and 6,139 women). We observed a significant interaction between sleep duration and physical activity in predicting death (P < 0.001). Long sleep duration (>8 hours) was associated with increased mortality risk (hazard ratio = 1.24; 95% confidence interval: 1.11, 1.39) and shorter survival (15th percentile difference = -20 months; 95% confidence interval: -30, -11) among only those with low physical activity. The association between long sleep duration and death might be partly explained by comorbidity with low physical activity.