Risk as a pattern over time: Delineation of time-dependent risk factors in biological,psychological, and social variables in cancer patients

Background

Survival in cancer patients is associated with a multitude of biological, social, and psychological factors. Although it is well established that all these factors add to overall mortality, it is not well understood how the predictive power of these parameters changes in a comprehensive model and over time.

Methods

Patients who attended the authors’ outpatient clinic were invited to participate. The authors followed 5180 mixed cancer patients (51.1% female; mean age, 59.1 years [SD = 13.8]) for up to 16 years and analyzed biological (age, sex, cancer site, anemia), psychological (anxiety, depression), and social variables (marital status, education, employment status) potentially predicting overall survival in a Cox proportional hazards model.

Results

The median survival time for the entire sample was 4.3 years (95% confidence interval, 4.0–4.7). The overall survival probabilities for 1 and 10 years were 76.8% and 38.0%, respectively. Following an empirical approach, the authors split the time interval into five periods: acute, subacute, short-term, medium-term, and long-term. A complex pattern of variables predicted overall survival differently in the five periods. Biological parameters were important throughout most of the time, social parameters were either time-independent predictors or tended to be more important in the longer term. Of the psychological parameters, only depression was a significant predictor and lost its predictive power in the long-term.

Conclusions

The findings of this study allow the development of comprehensive patient-specific models of risk and resilience factors addressing biopsychosocial needs of cancer patients, paving the way for a personalized treatment plan that goes beyond biomedical cancer care.     

Veno-arterial CO2 difference and lactate for prediction of early mortality after cardiac arrest

Patients admitted to intensive care after cardiac arrest are at risk of circulatory shock and early mortality due to cardiovascular failure. The aim of this study was to evaluate the ability of the veno-arterial pCO₂ difference (∆pCO₂; central venous CO₂ – arterial CO₂) and lactate to predict early mortality in postcardiac arrest patients. This was a pre-planned prospective observational sub-study of the target temperature management 2 trial. The sub-study patients were included at five Swedish sites. Repeated measurements of ∆pCO₂ and lactate were conducted at 4, 8, 12, 16, 24, 48, and 72 h after randomization. We assessed the association between each marker and 96-h mortality and their prognostic value for 96-h mortality. One hundred sixty-three patients were included in the analysis. Mortality at 96 h was 17%. During the initial 24 h, there was no difference in ∆pCO₂ levels between 96-h survivors and non-survivors. ∆pCO₂ measured at 4 h was associated with an increased risk of death within 96 h (adjusted odds ratio: 1.15; 95% confidence interval [CI]: 1.02–1.29; p = .018). Lactate levels were associated with poor outcome over multiple measurements. The area under the receiving operating curve to predict death within 96 h was 0.59 (95% CI: 0.48–0.74) and 0.82 (95% CI: 0.72–0.92) for ∆pCO₂ and lactate, respectively. Our results do not support the use of ∆pCO₂ to identify patients with early mortality in the postresuscitation phase. In contrast, non-survivors demonstrated higher lactate levels in the initial phase and lactate identified patients with early mortality with moderate accuracy.