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The pivotal role of hypoxia within the pathophysiological framework of solid malignant tumors is now considered to be indisputable. The fact that hypoxia can cause resistance to various cancer therapies and promote malignant progression is reflected in its adverse impact on prognosis which is repeatedly shown for various tumor entities. Knowledge in this area is based on direct assessment of the oxygenation status using O2-sensitive microsensors. However, weaknesses of this standard method are its invasiveness and limitation to accessible tumor entities. Hypoxia-inducible factor (HIF)-1α, the master transcriptional regulator of the hypoxic response, as well as certain downstream genes, e.g., glucose transporter (GLUT)-1 and carbonic anhydrase (CA) IX, have been considered to be suitable as surrogate biomarkers of hypoxia due to their tight regulation by O2 levels under certain, well-defined in vitro conditions. The fact that statistical correlations between the expression of these proteins and direct pO2 measurements in the clinic have been sporadically reported seemed to support their role as "endogenous hypoxia markers". Remaining disparities were mainly attributed to the influence of tumor heterogeneity. In a series of studies, we have addressed this question by examining the expression of HIF-1α, GLUT-1 and CA IX in tissue microareas where direct O2 measurements had previously been carried out, so that the influence of tumor heterogeneity could be reduced to a minimum. Using this methodology, no correlation between the expression of "endogenous hypoxia markers" and direct pO2 measurements could be found. In conclusion, while there may be a stringent association between these markers and the oxygenation status under standardized in vitro conditions, this is not transferable to the clinical assessment of oxygenation status in patients. The term "endogenous hypoxia markers" should therefore be avoided, at least in the clinical oncology setting. [ABSTRACT FROM AUTHOR]

Conspicuously high respiratory quotients (RQs) are found in solid tumors in vivo. RQs in the range between 1.29 and 1.95 neither reflect the degree of substrate oxidation by tumor cells nor indicate the types of fuels involved in metabolic processes. Instead, such tumor RQs most probably are caused by (a) channeling of glycolytic end-products into lipogenesis, and by (b) CO2 release from the tumor following extracellular buffering of H+ -inos by bicarbonate. H+ -inos exported from the intracellular space into the interstitial compartment titrate extracellular bicarbonate to CO2 and H2O with the aid of the ectoenzyme carbonic anhydrase IX, which is activated at low pH. Strikingly high (RQs) may thus be a further characteristic of the tumor microenvironment and of the tumor (patho-)physiome, the latter quantitatively describing the pathophysiologic characteristics of tumor cells and solid tumors. [ABSTRACT FROM AUTHOR]

The models and analyses of the preceding chapters have shown that senescence is not inevitable. Much more research is needed to understand why in some species mortality increases after maturity while in others it does not. My results raise an important new question for aging research: when does senescence vs. sustenance evolve? [ABSTRACT FROM AUTHOR]

The models developed in Chap. 4 show that non-senescence can be optimal. Size constitutes the central state variable in this framework. Mortality falls with increasing size and reproductive potential rises. The case of determinate growth, however, poses a challenge to this framework. Determinate growers, such as humans, often reach their final size at about the age of maturity. While size remains constant after the onset of reproduction, mortality steadily rises. This is incompatible with the strict size-dependence of mortality. A new model can be developed to address the deficiencies of the size-based model. To capture changing mortality at a constant size, the quality of size will be considered. The approach is rationalized in the following way. Even if size remains unchanged, all cells progressively accumulate damage over time and deteriorate. Vitality, defined as an individual's size adjusted for the functioning of body cells, can decline and therefore mortality can increase despite a constant body size. This notion was introduced in Sect. 4.4, where vitality was defined as the product of two functions, size and functioning. Here, vitality captures the accumulated functioning of all body cells, i.e. if a cell has been damaged and only works at 80 % of the capacity of an undamaged cell, this cell will account for 0.8 units of total vitality. [ABSTRACT FROM AUTHOR]

Hamilton did not prove that senescence is inevitable. Furthermore, it seems likely that the age-trajectory of mortality is largely shaped by optimization: only at advanced ages, when the bulk of total lifetime reproduction has been realized, might mutation accumulation play a role. So the question arises: could it be optimal for a species not to follow a senescent life-history strategy? [ABSTRACT FROM AUTHOR]

Hamilton's claim of the inevitability of senescence can be disproved even within his own framework. Furthermore, his framework has several limitations. In this chapter theoretical and empirical issues that weaken his approach as the main explanation for the evolution of senescence will be discussed. Building on Medawar [126] and Williams [212], Hamilton wrote the pioneering first chapter on the moulding of senescence. [ABSTRACT FROM AUTHOR]

To quantify the force of selection, Hamilton derived expressions for the change in fitness with respect to age-specific mutations. Hamilton's indicators are decreasing functions of age. He concluded that senescence is inevitable: survival and fertility must decline with age. I show that an alternative parametrization of mutational effects leads to indicators that can increase with age. I then consider the case of deleterious mutations with age-specific effects. In this case, it is the balance between mutation and selection pressure that determines the equilibrium number of mutations in a population. In this balance the effects of different parameterizations cancel out, but only to a linear approximation. I show that mutation accumulation has little impact at ages when this linear approximation holds. When mutation accumulation matters, nonlinear effects become important and the parameterizations of mutational effects make a difference. The results also suggest that mutation accumulation may be relatively unimportant over most of the reproductive lifespan of any species. [ABSTRACT FROM AUTHOR]

Death is part of life, and it can strike any time. The question is whether death necessarily becomes more likely as life proceeds. William D. Hamilton (1966), one of the leading biologists of the last century claimed that senescence is inevitable1 because the force of selection declines with age, making later ages unimportant to evolution. Survival and reproduction are the key players in this game and they are the traits negatively affected when selection loosens its grip. [ABSTRACT FROM AUTHOR]

To understand why mortality change can distort calculations of death rates and life expectancy, it is informative to consider some examples that are as simple as possible. This short chapter presents four such illustrations. They show how lifesaving can roil lifetable statistics. [ABSTRACT FROM AUTHOR]

The preceding chapters in this volume provide a broad ranging and stimulating analysis of our claim that conventional estimates of period life expectancy may be distorted by a mortality tempo effect. Much new insight into the process of mortality change and its measurement has been gained, but there is no clear consensus on the existence, nature and size of the tempo effect. Views from different contributors range widely from strongly supportive to dismissive. The purpose of this note is to comment briefly on the main question raised about our analysis of the mortality tempo effect: Is our tempo adjusted life expectancy a current measure of mortality conditions as we (and Vaupel in this volume p. 93 and Guillot in this volume) believe or a measure of the past as suggested by Rodriguez (in this volume) and Wachter (in this volume)? [ABSTRACT FROM AUTHOR]

What does tempo-adjusted period life expectancy measure? Taking a cohort perspective, I show that under conditions of constant linear mortality shifts the tempo-adjusted period indicator translates exactly to the cohort born e*0 (t) years earlier. I discuss the implications of cohort translation for the interpretation and application of tempo-adjusted period life expectancy. [ABSTRACT FROM AUTHOR]

This study provides a summary of recently proposed alternatives period measures of "longevity" and assesses whether empirical differences between these measures are consistent with predictions from analytic studies. Particular attention is given to the tempo effect. Three of the five period measures are virtually equal to one another in a simulated population in which mortality follows a Gompertz model with a constant rate of improvement. Similar results are observed among females in Denmark, England and Wales and Sweden in the last quarter century. However, these three measures differ substantially from the conventional period life expectancy when mortality changes over time. These findings are consistent with theoretical analysis by Bongaarts and Feeney (2002, in this volume p. 11 and p. 29) which demonstrated that this deviation is caused by a tempo effect whose size varies with the rate of change in mortality. [ABSTRACT FROM AUTHOR]

The number of scholars following the tempo approach in fertility continues to grow, whereas tempo-adjustment in mortality generally still is rejected. This rejection is irrational in principle, as the basic idea behind the tempo approach is independent of the kind of demographic event. Providing the first empirical application to a substantial problem, this chapter shows that mortality tempo-adjustment can paint a different picture of current mortality conditions compared to conventional life expectancy. An application of the Bongaarts and Feeney method to the analysis of mortality differences between western and eastern Germany shows that the eastern German disadvantages still are considerably higher and that the mortality gap between the two entities began to narrow some years later than trends in conventional life expectancy suggest. Thus, the picture drawn by tempo-adjusted life expectancy fits the expected trends of changing mortality and also the self-reported health conditions of eastern and western Germans better than that painted by conventional life expectancy. [ABSTRACT FROM AUTHOR]

It is widely known that shifts of cohort fertility schedule can produce misleading trends in period TFR. This note shows that such a "tempo bias" can occur in age-specific mortality as well: if the age distribution of cohort deaths shifts toward older (younger) ages, the period age-specific death rate is biased downward (upward). [ABSTRACT FROM AUTHOR]

We propose an alternative way of dealing with mortality tempo. Bongaarts and Feeney have developed a model that assumes a fixed delay postponing each death. Our model, however, assumes that changes take place with the removal of a given cause of mortality. Cross-sectional risks of mortality by age and expectations of life therefore are not biased, contrary to the model of the two authors. Treating the two approaches as two particular cases of a more general process, we demonstrate that these two particular cases are the only ones that have general properties: The only model enjoying a decomposable expression is the removal model and the only model enjoying the proportionality property is the fixed delay model. [ABSTRACT FROM AUTHOR]

This chapter introduces and develops the idea of "increments to life." Increments to life are roughly analogous to forces of mortality: they are quantities specified for each age and time by a mathematical function of two variables that may be used to describe, analyze and model changing length of life in populations. The rationale is three-fold. First, I wanted a general mathematical representation of Bongaart's "life extension" pill (Bongaarts and Feeney in this volume p. 11) allowing for continuous variation in age and time. This is accomplished in sections 3-5, to which sections 1-2 are preliminaries. It turned out to be a good deal more difficult than I expected, partly on account of the mathematics, but mostly because it requires thinking in very unaccustomed ways. Second, I wanted a means of assessing the robustness of the Bongaarts-Feeney mortality tempo adjustment formula (Bongaarts and Feeney in this volume p. 11) against variations in increments to life by age. Section 6 shows how the increments to life mathematics accomplishes this with an application to the Swedish data used in Bongaarts and Feeney (in this volume p. 11). In this application, at least, the Bongaarts-Feeney adjustment is robust. Third, I hoped by formulating age-variable increments to life to avoid the slight awkwardness of working with conditional rather than unconditional survival functions. This third aim has not been accomplished, but this appears to be because it was unreasonable to begin with. While it is possible to conceptualize length of life as completely described by an age-varying increments to life function, this is not consistent with the Bongaarts-Feeney mortality tempo adjustment. What seems to be needed, rather, is a model that incorporates two fundamentally different kinds of changes in mortality and length of life, one based on the familiar force of mortality function, the other based on the increments to life function. Section 7 considers heuristically what such models might look like. [ABSTRACT FROM AUTHOR]

This study examines the existence of tempo effects in mortality and evaluates the procedure developed by Bongaarts and Feeney for calculating a tempo-adjusted life expectancy. It is shown that the performance of Bongaarts and Feeney's index as an indicator reflecting current mortality conditions depends primarily on specific assumptions regarding the effects of changing period mortality conditions on the timing of future cohort deaths. It is argued that, currently, there is no clear evidence about the existence of such effects in actual populations. This chapter concludes that, until the existence of these effects can be demonstrated, it is preferable to continue using the conventional life expectancy as an indicator of current mortality conditions. [ABSTRACT FROM AUTHOR]

Bongaarts and Feeney offer alternatives to period life expectancy with a set of demographic measures equivalent to each other under a Proportionality Assumption. Under this assumption, we show that the measures are given by exponentially weighted moving averages of earlier values of period life expectancy. They are indices of mortality conditions in the recent past. The period life expectancy is an index of current mortality conditions. The difference is a difference between past and present, not a "tempo distortion" in the present. In contrast, the Bongaarts-Feeney tempo-adjusted Total Fertility Rate is a measure of current fertility conditions, which can be understood in terms of a process of birth-age standardization. [ABSTRACT FROM AUTHOR]

Mortality change roils period rates. In the short term, conventional calculations of age-specific probabilities of death and life expectancy in the period immediately after the change depend on how many lives have been saved. In the long term, the probabilities and period life expectancy also depend on how long these lives have been saved. When mortality is changing, calculations of period life expectancy do not, except in special circumstances, measure the life expectancy of a cohort of newborns that hypothetically live all their lives under the new mortality regime. [ABSTRACT FROM AUTHOR]

In this chapter I review the concept of tempo effects in demography, focusing on the tempo adjustments proposed by Bongaarts and Feeney and drawing on the work of Ryder and Zeng and Land. I show that the period-shift model that underlies the proposed adjustments can be motivated from an accelerated failure time cohort perspective. I propose alternative measures of tempo under changing fertility and mortality that share a synthetic cohort interpretation with the adjusted measure of quantum. I stress similarities between the results for fertility and mortality, particularly in terms of mean age of childbearing and mean age at death, but also note some important distinctions. I conclude that the fertility adjustments can help distinguish quantum and tempo effects, but argue that in the case of mortality the Bongaarts-Feeney measure of tempo-adjusted life expectancy differs from conventional estimates because if reflects past mortality. [ABSTRACT FROM AUTHOR]

This study develops and applies a general framework for the analysis of the period quantum and tempo of life-cycle events, extending methods developed previously by the authors. The existence of tempo distortions is demonstrated in selected period quantum measures such as the total fertility rate and in period tempo measures such as life expectancy. A tempo distortion is defined as an inflation or deflation of a period quantum or tempo indicator of a life-cycle event, such as birth, marriage, or death, that results from a rise or fall in the mean age at which the event occurs. Period measures derived from life tables are also found to be subject to tempo distortions. Methods to remove these tempo distortions are then developed and applied. [ABSTRACT FROM AUTHOR]

The life expectancy implied by current age-specific mortality rates is calculated with life table methods that are among the oldest and most fundamental tools of demography. We demonstrate that these conventional estimates of period life expectancy are affected by an undesirable "tempo effect." The tempo effect is positive when the mean age at death is rising and negative when the mean is declining. Estimates of the effect for females in three countries with high and rising life expectancy range from 1.6 yr in the U.S. and Sweden to 2.4 yr in France for the period 1980-1995. [ABSTRACT FROM AUTHOR]

The measurement of human longevity is one of the oldest topics in demography. The most widely used measure of longevity is the period life expectancy at birth which is calculated from age specific death rates by life table methods that originated with Graunt (1661) and have been standard in the field for well over a century. Period life expectancy equals the mean age at death in a synthetic cohort and it should be distinguished from the actual cohort life expectancies calculated for a group of individuals observed over long time periods. [ABSTRACT FROM AUTHOR]

In many highly developed countries, remarkable progress has been made in recent decades in reducing death rates, especially at older ages. New statistical data on mortality over time and up to the highest ages have revealed the time and age pattern of these improvements. These data have permitted reliable estimation of the age-trajectory of mortality, which turns out to follow a logistic pattern with deceleration at advanced ages. Individuals are heterogeneous with regard to their chances of death, and the frail tend to die first. Deeper understanding of the age-trajectory of mortality and the pattern of mortality improvements hinges on the development of statistical models that incorporate such mortality selection. This paper surveys the dynamics of mortality over age and time, reviews some "frailty model" approaches to analysing these dynamics, and presents some illustrative findings from studies of Danish twins and of the surface of Italian mortality over age and since 1895. Our goal is to participate in the debate on longevity from a demographic point of view and disclose the underlying features of accelerating human longevity. We are of the opinion that an analysis of this nature could help reveal the triggering factors. The study is a first step towards achieving this goal. [ABSTRACT FROM AUTHOR]

At very old ages mortality decelerates in developed countries. We show that this is also the case for China. We find that the Kannisto model, a two-parameter logistic formula, fits Han Chinese death rates at oldest-old ages better than the Gompertz and four other models. Chinese death rates appear to be roughly similar to Swedish and Japanese rates after age 97 for both males and females. Since reports of age appear to be serviceably reliable up to age 100 and perhaps age 105 in China, we think that this convergence may be mainly due to mortality selection in the heterogeneous Chinese population. [ABSTRACT FROM AUTHOR]