Vitality index in survival modeling: how physiological aging influences mortality

Preoperative Comprehensive Geriatric Assessment Predicts Postoperative Risk in Older Patients with Esophageal Cancer

BACKGROUND

Preoperative risk assessment is important in older patients because they often have comorbidities and impaired organ function. We performed preoperative comprehensive geriatric assessment (CGA) for older patients with esophageal cancer.

PATIENTS AND METHODS

A total of 217 patients over 75 years old who underwent esophagectomy for thoracic esophageal cancer were analyzed. The CGA was performed preoperatively and included the Mini-Mental State Examination (MMSE), Geriatric Depression Score (GDS), vitality index, Barthel index, and instrumental activities of daily living (IADL). We defined the robust group as patients with normal function on every instrument, and the pre-frail and frail groups as those with functional impairment on one instrument or two or more instruments, respectively. We assessed how the CGA correlated with postoperative complications and prognosis.

RESULTS

Of the 217 patients, 86 (39.6%) were in the robust group, 68 (31.3%) in the pre-frail group, and 63 (29.0%) in the frail group. Postoperative pneumonia (P = 0.026) and anastomotic leakage (P = 0.032) were significantly more common in the frail group. The frail group had a significantly longer postoperative hospitalization period (P = 0.016) and significantly lower rate of discharge to home (P = 0.016). Overall survival (OS) was significantly worse in the frail group (5-year overall survival rate, frail group versus others, 37.8% versus 52.0%, P = 0.046), but it was not significant on multivariate analysis.

CONCLUSIONS

The preoperative CGA in older patients with esophageal cancer was associated with risk of postoperative complications.

Aging in the context of cohort evolution and mortality selection

This study examines historical patterns of aging through the perspectives of cohort evolution and mortality selection, where the former emphasizes the correlation across cohorts in the age dependence of mortality rates, and the latter emphasizes cohort change in the acceleration of mortality over the life course. In the analysis of historical cohort mortality data, I find support for both perspectives. The rate of demographic aging, or the rate at which mortality accelerates past age 70, is not fixed across cohorts; rather, it is affected by the extent of mortality selection at young and late ages. This causes later cohorts to have higher rates of demographic aging than earlier cohorts. The rate of biological aging, approximating the rate of the senescence process, significantly declined between the mid- and late-nineteenth century birth cohorts and stabilized afterward. Unlike the rate of demographic aging, the rate of biological aging is not affected by mortality selection earlier in the life course but rather by cross-cohort changes in young-age mortality, which cause lower rates of biological aging in old age among later cohorts. These findings enrich theories of cohort evolution and have implications for the study of limits on the human lifespan and evolution of aging.

Lifespan and aggregate size variables in specifications of mortality or survivorship

A specification of mortality or survivorship provides respective explicit details about mortality's or survivorship's relationships with one or more other variables (e.g., age, sex, etc.). Previous studies have discovered and analyzed diverse specifications of mortality or survivorship; these discoveries and analyses suggest that additional specifications of mortality or survivorship have yet to be discovered and analyzed. In consistency with previous research, multivariable limited powered polynomials regression analyses of mortality and survivorship of selected humans (Swedes, 1760-2008) and selected insects (caged medflies) show age-specific, historical-time-specific, environmental-context-specific, and sex-specific mortality and survivorship. These analyses also present discoveries of hitherto unknown lifespan-specific, contemporary-aggregate-size-specific, and lifespan-aggregate-size-specific mortality and survivorship. The results of this investigation and results of previous research help identify variables for inclusion in regression models of mortality or survivorship. Moreover, these results and results of previous research strengthen the suggestion that additional specifications of mortality or survivorship have yet to be discovered and analyzed, and they also suggest that specifications of mortality and survivorship indicate corresponding specifications of frailty and vitality. Furthermore, the present analyses reveal the usefulness of a multivariable limited powered polynomials regression model-building approach. This article shows that much has yet to be learned about specifications of mortality or survivorship of diverse kinds of individuals in diverse times and places.

Sepsis progression and outcome: a dynamical model

Background

Sepsis (bloodstream infection) is the leading cause of death in non-surgical intensive care units. It is diagnosed in 750,000 US patients per annum, and has high mortality. Current understanding of sepsis is predominately observational and correlational, with only a partial and incomplete understanding of the physiological dynamics underlying the syndrome. There exists a need for dynamical models of sepsis progression, based upon basic physiologic principles, which could eventually guide hourly treatment decisions.

Results

We present an initial mathematical model of sepsis, based on metabolic rate theory that links basic vascular and immunological dynamics. The model includes the rate of vascular circulation, a surrogate for the metabolic rate that is mechanistically associated with disease progression. We use the mass-specific rate of blood circulation (SRBC), a correlate of the body mass index, to build a differential equation model of circulation, infection, organ damage, and recovery. This introduces a vascular component into an infectious disease model that describes the interaction between a pathogen and the adaptive immune system.

Conclusion

The model predicts that deviations from normal SRBC correlate with disease progression and adverse outcome. We compare the predictions with population mortality data from cardiovascular disease and cancer and show that deviations from normal SRBC correlate with higher mortality rates.

The mortality rate as a function of accumulated deficits in a frailty index

In a representative Canadian population survey (n=66589) the proportion of accumulated deficits in a frailty index showed a linear relationship with mortality in a log-log plot, such that the mortality rate was a power-law function of the frailty index. Represented in this way, the frailty index readily summarizes individual differences in health status. The exponent and amplitude parameters of the power function are gender specific, reflecting that while, on average, women accumulate more deficits than men of the same age, their risk of mortality is lower. The dependence of the mortality rate on the frailty index points to the merit of the index as a simple and accessible tool for estimating individual risks of mortality.