Psychosomatics 43:370-377, October 2002
© 2002 The Academy of Psychosomatic Medicine
Predicting the Trajectory of Will to Live in Terminally Ill Patients
Douglas Tataryn, Ph.D., and
Harvey Max Chochinov, M.D., Ph.D.
Received Jan. 18, 2002; revision received Feb. 16, 2002; accepted Feb. 16, 2002. From the Faculty of Nursing and the Division of Palliative Care of the Department of Psychiatry and Family Medicine, University of Manitoba, Winnipeg, Canada; and CancerCare Manitoba, Winnipeg, Canada. Address reprint requests to Dr. Chochinov, PX-246 771 Bannatyne Ave., Winnipeg, Canada, R3E 3N4; chochin{at}cc.umanitoba.ca (e-mail).
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ABSTRACT
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Will to live has been shown to vary considerably during the final course of a terminal illness. The goal of this study was to identify illness-related and demographic variables predicting will to live among dying patients. Subjects were 168 patients with cancer who were admitted for palliative care. Will to live was measured twice daily for the duration of hospitalization by using a self-report 100-mm visual analogue scale. Will-to-live data for each patient were summarized into two statistics, intercept and slope, by using simple linear regression analyses. Intercept-slope pairs for all patients were classified into the following five clusters by using spatial and conceptual criteria: patients with sustained high will to live (58%), patients with sustained moderate will to live (11%), patients with sustained low will to live (3%), will-to-live relinquishers (18%), and will-to-live acquirers (10%). Discriminant analyses revealed seven variables that accounted for 69% of the variance in cluster membership: anxiety, shortness of breath, nausea, length of survival from time of admission, having a diagnosis of colon cancer, having no religion, and living with a spouse.
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INTRODUCTION
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Will to live has been shown to vary considerably in relatively brief periods of time during the final course of a terminal illness.1 The correlates of fluctuation in will to live change as death draws nearer, with anxiety, depression, and physical symptom distress each in turn accounting for the greatest variance in advanced cancer patients' self-reported visual analogue scale ratings of will to live.
A number of critical questions regarding the nature of will to live remain unanswered. For example, are there discernible patterns in the fluctuation of will to live in terminally ill patients, and, if so, are there demographic or disease-specific factors that might help predict a given individual's progression of will to live over their course of illness? Care providers may well recognize some of these patterns among advanced cancer patients, including those who seem to maintain a high endorsement of will to live despite all adversity and those who seem to rapidly relinquish their will to live over the course of their final illness. Perhaps less common but of particular interest (given the debate concerning physician-assisted suicide and euthanasia1–6) are those patients who maintain a consistently low endorsement of will to live throughout their terminal course. This study examined the nature of these patterns and the predictors of trends in will to live among patients nearing the end of life.
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METHODS
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The ethical review committee of the University of Manitoba Faculty of Medicine approved this study. All patients gave written acknowledgment of informed consent before their participation. Patients were recruited from the Riverview Palliative Care Unit in Winnipeg, Manitoba. This unit admits patients on a voluntary basis for a variety of palliative care needs, including primarily symptom management, respite for patients and families, and terminal care. All patients admitted to the hospital during the study period had a primary diagnosis of terminal cancer. After admission, each patient was given 24–48 hours to accommodate to the ward routine before being approached for the study. The patient's medical status was then reviewed with the ward staff, and patients who were too cognitively impaired, weak, or ill to complete the daily assessments were considered ineligible and not approached for the study. When informed consent was obtained, patients were administered the Mini-Mental State Examination (MMSE).7 Those scoring  21 of 30—a cutoff threshold recommended in routine screening for cognitive impairment in elderly patients8—were then entered into the study.
Data were gathered with the Edmonton Symptom Assessment System.9 The Edmonton Symptom Assessment System is a self-report instrument consisting of a series of visual analogue scales designed specifically for use with palliative patient populations. The scales assess pain, anxiety, depression, sense of well-being, dyspnea, nausea, activity, drowsiness, and appetite. For this study, an additional will-to-live visual analogue scale—anchored by "complete will to live" and "no will to live"—was added. To maintain consistency across the different visual analogue scale items, a high score on any Edmonton Symptom Assessment System variable was considered to reflect heightened symptom intensity. Thus, a high will-to-live score indicated a low endorsement of will to live. All participants were asked to make a vertical mark indicating the intensity of the particular symptom at the point in time when the scale was completed. Each participant's symptom distress levels were measured twice daily (morning and late afternoon) from the time they entered the study until they could no longer provide data (even with the assistance of a research nurse), they died, or they were discharged from the unit. The MMSE was administered on entry into the study and once a week thereafter to monitor cognitive status and provide a validity check for data collected with the Edmonton Symptom Assessment System.
Analyses of the data followed a three-step process. First, the will-to-live data for each patient were transformed by using the Statistical Analyses Software (SAS, Cary, N.C.) least-squares linear regression procedure, yielding two parameters, the slope and the intercept. The slope parameters are unstandardized betas and interpretable as millimeters of change in the will-to-live score per 12-hour observation period. The intercept represents a calculated mean will-to-live score at time 0 (i.e., just before admission), given both the initial will-to-live scores and the subsequent average rate of change (slope) in will to live over the hospital stay. This technique, known as ideographic modeling, has been utilized in both the education10,11 and psychology12 literatures. Second, the slope and intercept data were plotted and grouped into clusters by using a combination of spatial and conceptual criteria (Figure 1). Construct definition of the intercept-slope clusters was confirmed statistically by using analysis of variance with Duncan's post hoc comparisons.
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FIGURE 1. Least-Squares Linear Regression Parameters for 164 Palliative Care Patients With Terminal Cancer Grouped in Clusters According to Trajectory of Will to Live
Note: Slope parameters are unstandardized betas interpretable as millimeters of change in the visual analogue will-to-live score per 12-hour observation period. Intercept parameters represent a calculated mean will-to-live score at time 0 (i.e., just before admission), given both the initial will-to-live scores and the subsequent average rate of change (slope) in will to live over the hospital stay.
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Finally, discriminant analyses were used to determine the extent to which membership in each intercept-slope cluster could be predicted by patient demographic variables and initial symptom characteristics. Dummy variables were created from each demographic variable, coded 0 and 1 against the most common or conceptually distinct value. These variables, including age, sex, marital status, religious affiliation, and primary diagnosis, as well as admission values for symptom distress (pain, anxiety, depression, sense of well-being, dyspnea, nausea, activity, drowsiness, and appetite), were allowed to enter stepwise into the discriminant analysis predicting cluster grouping.
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RESULTS
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As previously reported,1 a total of 585 admissions occurred during the course of data collection. One hundred fifty-three patients (26.2%) were not referred to the study because the initial screening determined they were cognitively impaired and/or too weak or ill to participate. Thirty-nine patients (6.7%) were found to be ineligible, as they scored below the critical threshold of  21 of 30 on the MMSE. One hundred forty-eight patients (25.3%) admitted to the unit refused to participate in the study. Seventy-seven patients (13.2%) were otherwise unavailable. Thus, the final group of 168 admissions—ranging in age from 31 to 89 years—represented 28.7% of the total possible sampling frame.
Fifty-one percent of the 585 patients admitted during the study period were male. Forty-eight percent were married, 30% were widowed, 9% were single, 8% were divorced, and 5% had other marital statuses. Forty-eight percent lived with a spouse before admission, 35% lived alone, 8% lived with a child, and 9% had other living arrangements. The study participants and nonparticipants were similar in gender, marital status, and previous living arrangements. Consistent with the fact that more than 55% of the nonparticipants either died before the study began or were too ill or cognitively impaired to participate, there were significant differences in age and survival time between the two groups. Those who participated in the study were slightly younger (68 versus 71 years old) (t=3.16, df=336.6, p<0.001) and lived an average of almost 18 days or 50% longer than those who did not participate (t=3.13, df=571.0, p<0.002). Median duration of survival was 31.5 and 15.0 days for the participants and nonparticipants, respectively.
Neoplasms of the digestive and respiratory systems accounted for more than 50% of admissions. The nonparticipants and participants differed in diagnosis at time of admission ( 2=20.44, df=8, p<0.009), with tumors of the lung (26% versus 36%, respectively), brain (5% versus 1%), and other (15% versus 8%) constituting over 80% of the total chi square. The higher prevalence of brain tumors among the nonparticipants is not surprising, given that such lesions often render patients cognitively ineligible to participate. There were significant differences between the two groups in release status at the end of the hospital stay (2=13.05, df=2, p<0.001); 68% of participants were deceased at the end of their hospital stay compared to 81% of nonparticipants. Among patients who participated in the study, the mean length of time in the protocol was 21.6 days (SD=27.1). Completed Edmonton Symptom Assessment System data were gathered to within 1 day (median) of death.
Regression Modeling of Will-to-Live Trajectories
A total of 168 slope and intercept pairs were derived from the will-to-live data, one pair for each patient in the study. The correlation between the intercept and the will to live at study entry was r=0.80. The average intercept and slope values for the patients were 18.5 (SD=27.5) and 0.55 (SD=7.7), respectively. Thus the "average" patient in the study initially had a strong will to live and slowly relinquished this will to live at an average rate of 1.1 mm per day. Note that the large standard deviations indicate that there was considerable variability from this average depiction.
Figure 1 shows a point-plot of the slope and intercept parameters derived for each patient. Points to the right of zero along the horizontal (slope) axis represent patients who relinquish will to live with the passage of time. Points to the left of zero along the slope axis represent patients who acquire will to live over time, and points near or at zero represent patients who reveal little or no change in will to live over time. The vertical axis represents the will to live intercept value. After the axis is divided into thirds, the lower third (will-to-live scores of 0–33 mm) represents patients who report a strong will to live, the upper third (will-to-live scores of 67–100) represents those with a very low will to live, and the middle third (will-to-live scores of 34–66) represents those who maintained a moderate endorsement of will to live. Four slope-intercept data points were eliminated as outliers and deleted from subsequent analyses (one with a slope of less than -50 mm/day and three with intercepts of less than -20). Each deleted outlier was based on three or fewer observation points.
Five intercept-slope clusters emerged from the analysis.
- Patients with sustained high will to live (N=95; 58%): This group, representing the majority of intercept-slope points, was defined by clustering near 0 on the slope axis (less than 2 mm of change per day in either direction) and having an intercept falling within the lower third of the will-to-live intercept axis (will-to-live score range=0–33 mm; i.e., the highest endorsement of will to live). Figure 2 shows the will-to-live ratings over the course of the admission and the intercept and slope parameters of the trajectory of will to live for a patient in this group.
- Patients with sustained low will to live (N=5; 3%): This small group of patients endorsed a will to live score of greater than 67 mm and maintained a lack of will to live throughout their admission. They were defined by intercept-slope points that clustered near 0 on the slope axis (less than 2 mm of change per day in either direction) and having an intercept falling within the upper third of the will-to-live intercept axis (will-to-live score range=67–100 mm). Figure 3 shows the will-to-live ratings over the course of the admission and the intercept and slope parameters of the trajectory of will to live for a patient in this group.
- Patients with sustained moderate will to live (N=19; 11%): This group of patients largely endorsed moderate will-to-live scores (neither consistently high nor low scores) throughout their admission. They were defined by intercept-slope points that clustered near 0 on the slope axis (less than 2 mm of change per day in either direction) and having an intercept falling within the middle third of the will-to-live intercept axis (will-to-live score range=34–66 mm). Figure 4 shows the will-to-live ratings over the course of the admission and the intercept and slope parameters of the trajectory of will to live for a patient in this group.
- Will-to-live relinquishers (N=29; 18%): This group of patients relinquished will to live at a rate of 2 mm or more per day. Figure 5 shows the will-to-live ratings over the course of the admission and the intercept and slope parameters of the trajectory of will to live for a patient in this group.
- Will-to-live acquirers (N=16; 10%): This group of patients increased their will to live at a rate of 2 mm or more per day. Figure 6 shows the will-to-live ratings over the course of the admission and the intercept and slope parameters of the trajectory of will to live for a patient in this group.
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FIGURE 2. Will-to-Live Ratings and Least-Squares Linear Regression Parameters of the Trajectory of Will to Live for a 71-Year-Old Male Patient With Lung Cancer and Sustained High Will to Live
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FIGURE 3. Will-to-Live Ratings and Least-Squares Linear Regression Parameters of the Trajectory of Will to Live for an 86-Year-Old Male Patient With Lung Cancer and Sustained Low Will to Live
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FIGURE 4. Will-to-Live Ratings and Least-Squares Linear Regression Parameters of the Trajectory of Will to Live for a 71-Year-Old Female Patient With Lung Cancer and Sustained Moderate Will to Live
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FIGURE 5. Will-to-Live Ratings and Least-Squares Linear Regression Parameters of the Trajectory of Will to Live for a 59-Year-Old Male Patient With Lung Cancer Classified as a Will-to-Live Relinquisher
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FIGURE 6. Will-to-Live Ratings and Least-Squares Linear Regression Parameters of the Trajectory of Will to Live for a 78-Year-Old Female Patient With Colon Cancer Classified as a Will-to-Live Acquirer
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The analysis of variance for intercept (F=104.19, df=4, 160, p<0.0001, r2=0.72) and slope (F=28.21, df=4, 160, p<0.0001, r2=0.42) were both statistically significant. Duncan's post hoc comparison demonstrated three distinct intercept groupings: 1) patients with sustained low will to live, 2) will-to-live acquirers and patients with sustained moderate will to live, and 3) patients with sustained high will to live and will-to-live relinquishers (p<0.05). Patients with a sustained low will to live had an average intercept of 94 mm and a slope near 0. The will-to-live acquirers and the patients with sustained moderate will to live had average intercepts of 45 mm and statistically different slopes of –6.2 and –1.2 mm/day, respectively (p<0.05, Duncan's test). Sustained high will to live and will-to-live relinquishers had average intercepts of 8 mm and statistically different average slopes of 0.08 and 11.2 mm/day, respectively (p<0.05, Duncan's test).
Predicting Intercept-Slope Cluster Membership
A total of seven variables met the criterion for entry into the discriminant analysis model (p0.05). These variables accounted for a total of 69% of the variance of group membership (Table 1). Anxiety, shortness of breath, and nausea each accounted for approximately 10%–15% of the variance. Total length of survival from admission, a diagnosis of colon cancer, having no religion, and living with a spouse each accounted for approximately 8%–9% of the variance. Membership in the cluster with sustained lack of will to live was most accurately predicted (80%); 66% and 63% of the will-to-live acquirers and the patients with sustained high will to live, respectively, were correctly classified. The model correctly classified 39% of the will-to-live relinquishers and 21% of those with a sustained moderate will to live.
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TABLE 1. Stepwise Discriminant Analysis of Variables Predicting Membership of Palliative Care Patients With Terminal Cancer in Clusters According to Trajectory of Will to Live
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Examination of the univariate relationships between the variables identified as significant in the discriminant analyses and the slope-intercept clusters is also revealing (Table 2). Patients who acquired will to live over their hospital course had the highest prevalence of colon cancers (37.5%; almost six times that of the group with sustained high will to live) and were admitted with the highest levels of nausea (mean=30.9 [SD=33.6]; twice the average level of the other groups). These patients were most likely to be living with a spouse (68.8%; almost twice the proportion of subjects in the group with sustained high will to live) and most likely not be religious (31.3%; twice the proportions of nonreligious subjects in the other groups).
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TABLE 2. Mean Scores and Category Status for Variables Predicting Membership of Palliative Care Patients With Terminal Cancer in Clusters According to Trajectory of Will to Live
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Those with sustained high will to live had the lowest levels of anxiety (mean=15.1, SD=21.5), were more likely to be religious (percent nonreligious 7.4%, approximately half that of the other groups), and had the lowest prevalence of colon cancer (49% of the expected prevalence). By contrast, the group with sustained low will to live had the highest levels of anxiety (mean=52, SD=44.1; more than three times that of the group with sustained high will to live), the highest levels of dyspnea (mean=83.4, SD=29.6, approximately three times that of the other groups), and the lowest rate of living with a spouse (0%). They also had the shortest survival times (measured in number of days from study entry until time of death; mean=28.4 days, SD=21.0), compared to the group with sustained moderate will to live, who demonstrated the longest average survival times (mean=109.3 days, SD=127.0).
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DISCUSSION
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Despite its importance in end-of-life care, the construct "will to live" has received surprisingly little attention. Although we recently reported that will to live can fluctuate considerably in the context of approaching death and that the causes of such fluctuation shift as death draws nearer, many questions remain unanswered. In this further analysis of our will-to-live data set, several important additional findings have emerged. It appears that five distinct groups of patients with different patterns of will to live can be identified. These groups consist of patients who maintain a high endorsement of will to live as death draws nearer (sustained high will to live), those who maintain a modest endorsement of will to live (sustained moderate will to live), those who maintain a low or poor endorsement of will to live (sustained low will to live), those who lose their will to live (will-to-live relinquishers), and those who gain will to live (will-to-live acquirers). As previously indicated, the majority of patients in this study had a strong will to live that was only slowly relinquished over time. The fact that the majority of patients (N=95; 58%) were classified in the group with sustained high will to live confirms that most patients, even toward the end of life, manage to maintain a strong will to live. As such, for most, the wish to go on living appears to be a resilient mind-set, even among those nearing death.
The five distinct clusters identified in the study were not only conceptually meaningful but also statistically confirmed by regression models that accounted for a robust portion of the variance in both the intercept and the slope values. The robustness of the cluster model was further confirmed by the extent to which the discriminant analysis accurately predicted cluster membership, especially for the patients with sustained low will to live, will-to-live acquirers, and the patients with sustained high will to live. Having established the construct definitions of these five patterns of will-to-live fluctuation, the discriminant analysis illustrated the distinguishing characteristics of each unique cluster. The group with sustained high will to live—the cluster subsuming the majority of patients in the study—was characterized by low anxiety and a higher level of endorsement of religious affiliation. These results suggest that finding ways to control anxiety, along with providing or enabling religious and spiritual support, are important components of high-quality end-of-life care. By way of contrast, the group with sustained low will to live reported the highest levels of both anxiety and dyspnea; none of these patients were reported to be living with a spouse, compared to at least 50% of patients in the other will-to-live clusters. This suggests that the patients with sustained low will to live were both highly symptomatic and perhaps lacking in social support. Both of these variables have been reported in prior studies addressing patients' interest in physician-assisted suicide4–6,13 and endorsement of desire for death among terminally ill patients.14 Although the patients in this study were not specifically asked about their wishes for a hastened death, one can assume that the patients in the sustained low will-to-live cluster, i.e., competent individuals with a continuous low endorsement of will to live, would be those at the heart of the debate about the right of dying patients to control the timing and circumstances of their death. These findings reinforce the importance of vigilant symptom management and of bolstering social support for patients who no longer see life as worth living.
The will-to-live acquirers had the highest prevalence of colon cancer and the highest self-report nausea scores. Nausea is a symptom that is particularly amenable to pharmaceutical and therapeutic interventions.15 The high nausea scores among will-to-live acquirers suggest that even for those nearing death, symptom relief—such as the alleviation of nausea in a patient with an advanced gastrointestinal malignancy—might help patients reestablish a waning will to live. Finally, patients with moderate sustained will to live were found to have the longest survival times, whereas patients in the sustained low will to live cluster died soonest. While these results are intriguing, one can only speculate about the association between will to live and longevity on the basis of these data. Our findings are nevertheless consistent with prior studies demonstrating that individuals who no longer anticipate events with symbolic significance—anticipation that might bolster ones will to live—in fact die sooner.16,17
As in any study, there are important limitations to be considered. The patient group was composed mostly of older individuals, all of whom were in an advanced stage of terminal cancer. Hence, it is not clear that the findings would be comparable with those for younger populations or for patients dying from other illnesses, such as AIDS, progressive neuromuscular disorders, or advanced cardiac or respiratory conditions. The study group was also restricted to individuals who were mentally competent and well enough to fill out the twice-daily self-report measures. This group constituted a minority of patients admitted to the participating palliative care unit. However, the issue of will to live is most salient and accessible among patients who maintain relative cognitive intactness. In considering the cluster groupings of will to live, it should be borne in mind that regression models are equivalent to average ratings and take into account the trend for ratings to increase or decrease over time. While this approach may not allow clinicians to anticipate the day-to-day fluctuations in will to live that can and do occur,1 it does provide an indication of the general pattern or trend they might expect in the trajectory of their dying patients' will to live.
Tracking will to live, whether as part of or independent of the Edmonton Symptom Assessment System, may be an important consideration for those who care for dying patients. Doing so may further our understanding of the association between patient characteristics, disease-specific variables, and the different patterns of will-to-live fluctuation that occur near the end of life. Measuring and tracking will to live provides an indication of the extent to which patients see life as being worthy of living. As such, will to live may be an important outcome measure that may sensitize clinicians to patients' care needs. Developing reliable outcome measures is crucial to the task of improving palliative care9,18,19 and will no doubt lead to better care for patients nearing death.
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ACKNOWLEDGMENTS
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This work was supported by grants from the National Cancer Institute of Canada with funding from the Canadian Cancer Society and from the Project on Death in America of the Open Society Institute. The authors thank Dr. D. Dudgeon and Dr. J. Clinch for comments on earlier drafts of this manuscript.
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REFERENCES
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- Chochinov HM, Tataryn D, Dudgeon D, Clinch J: Will to live in the terminally ill. Lancet 1999; 354:816-819[Medline]
- Foley KM: Competent care for the dying instead of physician-assisted suicide. N Engl J Med 1997; 336:54-58
- Angell M: The Supreme Court and physician-assisted suicide—the ultimate right. N Engl J Med 1997; 336:50-53[Free Full Text]
- Steinhauser KE, Christakis NA, Clipp EC, McNeilly M, McIntyre L, Tulsky JA: Factors considered important at the end of life by patients, family, physicians, and other care providers. JAMA 2000; 284:2476-2482[Abstract/Free Full Text]
- Wilson KG, Scott JF, Graham ID, Kozak JF, Chaters S, Viola RA, deFaye BJ, Weaver LA, Curran D: Attitudes of terminally ill patients toward euthanasia and physician-assisted suicide. Arch Intern Med 2000; 160:2454-2460[Abstract/Free Full Text]
- Emanuel EJ, Fairclough DL, Emanuel LL: Attitudes and desires related to euthanasia and physician-assisted suicide among terminally ill patients and their caregivers. JAMA 2000; 284:2460-2468[Abstract/Free Full Text]
- Folstein MF, Folstein SE, McHugh PR: "Mini-Mental State": a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975; 12:189-198[CrossRef][Medline]
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- Rogosa DR, Willett JB: Understanding correlates of change by modeling individual differences in growth. Psychometrika 1985; 50:203-228
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- Petrinovich L, Widaman KF: An evaluation of statistical strategies to analyze repeated-measures data, in Habituation, Sensitization, and Behavior. Edited by Peeke HVS, Petrinovich L. Orlando, Fla, Academic Press, 1984, pp 156-200
- Breitbart W, Rosenfeld BD, Passik SD: Interest in physician-assisted suicide among ambulatory HIV-infected patients. Am J Psychiatry 1996; 153:238-242[Abstract/Free Full Text]
- Chochinov HM, Wilson KG, Enns M, Mowchun N, Lander S, Levitt M, Clinch JJ: Desire for death in the terminally ill. Am J Psychiatry 1995; 152:1185-1191[Abstract/Free Full Text]
- Bruera E, Neumann CM: Management of specific symptom complexes in patients receiving palliative care. Can Med Assoc J 1998; 158:1717-1726[Abstract]
- Phillips DP, Smith DG: Postponement of death until symbolically meaningful occasions. JAMA 1990; 263:1947-1951[Abstract]
- Phillips DP, King EW: Death takes a holiday: mortality surrounding major social occasions. Lancet 1988; 2:728-732[CrossRef][Medline]
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ABSTRACT
INTRODUCTION
