The relationship of psychosocial factors to prognostic indicators in cutaneous malignant melanoma

JoourwlofPsychosomafic Printed in Great Britain.

Research,

Vol.

29, No.

THE RELATIONSHIP PROGNOSTIC

2, pp.

139-153,

0022-39V9/85 13.00+ .@I 0 1985 Pergamon Press Ltd.

1985.

OF PSYCHOSOCIAL INDICATORS

MALIGNANT

FACTORS

TO

IN CUTANEOUS

MELANOMA

LYDIA TEMOSHOK*, BRUCE W. HELLER*, RICHARD W. SAoEaIELt$z, MARDSEN S. Br.oIst$, DAVID M. SWEET*, RALPH J. DICLEMENTE* and MARC L. GOLD 11 (Received 14March

1984; accepted in revisedform 27 August 1984)

Abstract-This study investigated the relationship between prognosis (estimated by histopathologic indicators) in cutaneous malignant melanoma and a comprehensive set of physical risk, demographic, psychosocial, and situational variables. These variables were derived from the medical examination, the pathology report, psychosocial self-report measures, and an hour-long videotaped interview with 59 patients from two melanoma clinics in San Francisco. Variables significantly correlated with tumor thickness were: darker skin/hair/eye coloring, longer patient delay in seeking medical attention, two correlated dimensions within an operationally defined ‘Type C’ constellation of characteristics, two character style measures, and less previous knowledge of melanoma and understanding of its treatment. Of these variables, delay was the most significant in a hierarchical multiple regression analysis in which tumor thickness was the dependent variable. Associations between tumor thickness and psychosocial measures of Type C were considerably stronger and more significant for subjects less than age 55, suggesting that the role of behavioral and psychosocial factors in the course of malignant melanoma is more potent for younger than for older subjects. INTRODUCTION PREVIOUS research on the relationship of stress and psychosocial factors in humans to cancer may be divided into seven main categories, which are presented along with illustrative although not exhaustive examples: 1. ‘Somatopsychic’ studies of psychosocial sequelae of cancer and its treatment [e.g., l-41; 2. Cross-sectional studies comparing psychosocial characteristics of cancer patients with those of non-cancer controls [e.g., 5-101; 3. Predictive studies in which characteristics of individuals with suspicious lesions/lumps are assessed before a biopsy is performed and then compared with post-biopsy outcome [e.g., 1 l-141; 4. Prospective or retro-prospective studies of prior stress, premorbid psychosocial characteristics, and/or health habits associated with later cancer initiation [e.g., 15-221;

5. Longitudinal studies of individuals diagnosed with cancer, relating stress and/or psychosocial factors to disease progression/survival time [e.g., 23-281; 6. Studies relating physiological-particularly immunological-variables that are presumably associated with cancer initiation or exacerbation to psychosocial factors [e.g., 26, 29, 301; *Department of Psychiatry. TDepartment of Dermatology. *Department of Pathology. §Section on Medical Information Sciences, Francisco, CA 94143, U.S.A. /ISchool of Education, University of California, Correspondence and requests for reprints should Institute Box 6-B, 401 Parnassus, San Francisco,

University

of

California

School

Berkley, CA, U.S.A. be sent to: Dr. Lydia Temoshok CA 94143, U.S.A. 139

of

Medicine,

at the Langley

San

Porter

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L.TEMOSHOK etal.

7. Studies of psychosocial factors influencing delay in seeking medical treatment for cancer or cooperation with medical regimens [e.g., 31-361. It is not the purpose of the present commentary to discuss more extensively any of these studies; there exist several excellent reviews and critical evaluations of aspects of this literature [37-421. Rather, the intention of citing and categorizing these studies is to highlight a gap in this literature: studies relating psychosocial factors to stage of disease or the degree of cancer severity. There are only a few reports finding a significant relationship between specific behaviors and medical outcome [36, 43, 441. Further, it should be noted that these studies are limited to one type of cancer-breast, and one psychosocial variable-delay in seeking treatment. The present study was undertaken to address the need for studies relating psychosocial factors to cancer severity. Malignant melanoma presents several advantages for this focus of investigation in terms of the existence of precise and reliable staging systems for defining extent of disease. For the past decade, the prognosis for malignant melanoma has been estimated from a combination of clinical and histologic factors. The most important of these factors is tumor invasion, measured by the anatomic level [45], or more reliably by the maximal vertical thickness of the tumor [46]. The 5-yr survival rate of patients decreases progressively with either increasing level of dermal invasion or thickness of the primary tumor [47]. Cutaneous melanoma is a tumor arising from the pigment-producing cells in the skin. Unlike other types of skin cancer it has a substantial likelihood of metastatic spread. In recent years, there has been a sharp increase in observed incidence of morbidity [48], and to a lesser extent, mortality in malignant melanoma. Incidence has doubled within the past decade, increasing about 6% annually. This rate is second only to bronchogenic carcinoma in Caucasian women [49]. This change seems to be independent of better medical care, improved diagnosis, or more accurate certification [48]. Intermittent overexposure to ultraviolet radiation, and a fair, freckled, and easilyburned skin type, are factors implicated in the etiology of malignant melanoma [50]. The exact causes, however, remain unclear [51]. No other external agents have been identified, although a subset of melanomas can be linked to genetic factors [52]. Little attention has been directed towards psychosocial factors that might have prognostic significance. Several recent studies, however, are noteworthy. Rogentine et al. [27] found that patients with clinical stage I or II malignant melanoma, who minimized the amount of personal adjustment needed to cope with melanoma and surgical treatment, were more likely to relapse within one year (total n = 3 1). Using this measure of denial as a criterion, these investigators successfully predicted relapse in 76% of a second consecutive group (n = 33). Cassileth et al. [53] focused on a different variable: patient delay in seeking medical attention. They found no correlation between delay and tumor thickness in 245 patients with superficial spreading melanoma. The present study was concerned with the relationship between histopathologic indicators in malignant melanoma and certain psychosocial variables suggested by predictive and longitudinal studies in categories 3, 5, and 6 above which include some measure of medical status as a dependent variable. Such studies are relevant to the present research, in which all subjects already have melanoma and the

Psychosocial

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141

investigation focused on what variables are associated with unfavorable prognostic indicators. We also wanted to widen the scope of psychosocial variables beyond that of the strictly behavioral (i.e., delay) to incorporate some of the factors suggested by studies in these relevant categories. Recently, Temoshok and Heller [54] developed the notion of a ‘Type C’ individual who is cooperative, unassertive, patient, who suppresses negative emotions (particularly anger), and who accepts/complies with external authorities. This description is the polar opposite of the Type A behavior pattern which has been demonstrated to be predictive of coronary heart disease [e.g., 551 and differs from the Type B behavior pattern, which is defined as the absence of Type A characteristics. Hypothetically, we (L. Temoshok and B. W. Heller) would array these three constructs along a single dimension, ranging from the predominance of Type A to the predominance of Type C characteristics. The Type C construct is partly derived from the literature in psychosocial oncology mentioned above and is in accord with several authors who have previously used the term ‘Type C’ to refer to a cancer-prone personality as the opposite of the Type A pattern [56, 571, to a pattern of emotional constraint, particularly in the face of stress [58], or to a helpless-hopeless personality with depressive tendencies [59]. None of these authors, however, has explicitly operationalized dimensions of such a Type C construct, nor subjected the construct to testing in a psychosocial study of cancer patients. For the present study, the Type C construct was defined operationally as a constellation of (a) attitudes, (b) cognitive and emotional proclivities, (c) verbal and nonverbal expressive patterns, (d) specific coping strategies, and (e) more general character styles. These various dimensions were assessed by measures obtained through a structured interview and several self-report instruments. To the extent that predictive and longitudinal studies have found certain psychosocial factors akin to dimensions in our Type C constellation to be associated with malignant versus benign lesions or with worse versus better outcomes, it was hypothesized that Type C dimensions would be associated with unfavorable versus favorable prognostic indicators. In addition, it was hypothesized that the association of certain Type C dimensions and prognostic indicators would be stronger for younger versus older subjects. This hypothesis is based on theory and research by several authors [5, 41, 60, 611 who have reasoned that if psychosocial factors play a role in the initiation and/or course of cancer, then this role will be more evident in younger subjects for whom the disease process would be presumably less influenced by long-term exposure to environmental risk factors, or by age-related deterioration of the immune system. Finally, logic suggested that longer patient delays in seeking treatment would be associated with more unfavorable prognostic indicators. METHODS Subjects

Patients are referred from all over Northern California to the Malignant Melanoma Clinics at the University of California and Children’s Hospital in San Francisco for confirmatory diagnosis and treatment recommendations. Eligibility requirements for the present study were: (a) 18 yr or older, and (b) clinical stage I or II cutaneous malignant melanoma. All eligible patients seen at these two clinics between 3-31-80 and 10-13-80 were, on their first clinic visit, asked to participate in the present study. Fifty-nine patients-more than 90% of those asked-agreed to be subjects. Of the 59 subjects, 49 were in clinical stage I, and 10 were in clinical stage II (regional lympth node

L. Ta~osnorc

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et al.

involvement). All patients were seen within a month of biopsy. Subjects ranged in age from 18 to 72 yr; 48% fell within the age range 30 to 49. Sex distribution was 55% male and 45% female, which is comparable to other large-scale study samples [62, 631. All subjects were Caucasian. Patients’ occupational status (or if not currently employed, their pre-retirement position or their spouse’s occupation) was rated on a ‘I-point scale ranging from ‘professional’ to ‘unskilled’. The sample was fairly normally distributed, with 19% categorized as ‘professional’ or ‘semi-professional’, 52% falling in the managerial, small business, sales, and skilled worker ranks; and 29% in ‘semi-skilled’ or ‘unskilled’ occupations.

Measures and procedures Histopathology. Each patient was initially interviewed

and examined by a physician and the case was reviewed by the clinic consultants. Two histopathologic indices were rated by examination of the biopsy material: Clark’s level [45], and Breslow’s thickness criterion [46]. These two attributes were correlated + 0.71 @ < 0.0001) in this sample. All biopsy specimens were reviewed by a single pathologist (R.W.S.). Both measures of tumor invasion were used in the present study because of the as-yet unresolved controversy about which measure is more reliable and has greater predictive validity for survival [e.g., 641. Tumor thickness is, however, more commonly used and presumed to be superior [e.g., 651; therefore, it is more relied upon as a dependent variable for analyses reported in this study. Physical risk. Eye and hair coloring were rated separately by the psychosocial interviewers (who were blind to histopathology results) on 5-point scales of increasing pigmentation. Skin coloring was rated on a 5-point scale from reddish-pale to dark by the first author on the basis of notes in the medical record by the examining physician, who was able to inspect typically unexposed skin areas (usually underside of the forearm). A composite scale of ‘at-risk’ complexion included these three attributes plus a scale of relative number of freckles (also derived from the medical record). The structured videotaped interview. Patients were interviewed for about one hour on videotape by a clinical psychologist (L.T. or B.W.H.) following the physical examination. This structured interview inquired about (a) circumstances surrounding the patient’s suspicion about a symptom or lesion; (b) how and when the patient sought medical attention after noticing a symptom or change in the lesion; (c) the patient’s thoughts about and emotional reactions to the diagnosis of melanoma, cancer, and general health/illness issues; (d) behaviors used to cope with current medical problem; (e) unusual stressful situations within the previous 5 yr and how these were dealt with; and (f) coping with everyday stresses and strains. The videotapes were later rated according to a precise coding manual (available upon request from the first author) by masters-level psychologists (R.J.D., M.L.G. and Ms. Judy Curtiss) who were uninformed as to patient’s medical status. Because the coding format was highly structured, interrater reliabilities were quite high across all attributes, generally ranging from 87-99% agreement between observers (with one low 58% agreement on an item that was not used, therefore, in the data analyses). ‘Delay’ was defined as the interval, in months, from a patient’s report of first noticing a suspicious symptom or lesion to the date of consultation with a physician specifically about the lesion. It should be emphasized that ‘suspicious’ refers to the patient’s subjective impression, not to objective characteristics of the lesion, which differed across tumor subtypes. Variables from the structured interview were aggregated into 15 indices on an apriori theoretical basis by the first author. Statistical aggregation of the variables was accomplished independently using a principal axis factor analysis with a varimax rotation. The theoretical and factor analytic methods yielded very similar clusters of variables. The variables in two of the theoretically derived scales were not, however, related in the same orthogonal factors; therefore, these two a priori scales were deleted. Cronbach’s coefficient alpha [66, 671 which is generally regarded as the most satisfactory measure of reliability (internal consistency) was computed on the factor analytically derived groupings of variables. Variables were deleted if doing so increased coefficient alpha by at least 0.10. The final 13 scales produced by the procedure above are described in Table I. Self-report instruments. After the interview, subjects were given a packet of self report instruments, and asked to complete them within a day and mail them back to the principal investigator. These instruments included*: Beck’s Depression Inventory [68], the Psychological Distress Scale from the M.M.P.I. [69], McNair’s Profile of Mood States (POMS) [70], and Temoshok’s Character Style Inventory [71]. With the exception of the latter, which is in the process of validation, there is an extensive literature on reliability, validity, and standardization of these measures. The return rate was 73%. Subjects who returned questionnaires were compared with those who did not on all the sca!es derived from the interview and for tumor thickness, level of invasion, sex, age, occupational status, and delay. There were no significant differences between groups except for the scale ‘Coping with Strength’, on which subjects who returned questionnaires scores significantly higher @ < 0.04), and for the scale ‘Nonverbal Type C’, on which subjects who returned questionnaires scored lower, but not significantly so (p < 0.07). *Other self-report publication.

instruments

were also administered;

these results

will be reported

in a separate

Psychosocial

factors

and melanoma

prognostic

indicators

143

TABLE ~.-SUMMARYOFPSYCHOLOGICALSCALESDERIVEDFROMSTRUCTUREDINTERVIEW

Scale name and description

Coefficient

alpha

Items composing

scale

(Number in parentheses correlation)

is corrected

item-total

1. Catastrophic reaction: melanoma has disturbed most areas of functioning and provoked dire thoughts.

0.87

-Overestimates seriousness of melanoma (0.50).* -Number of symptoms of stress response, e.g., loss of appetite, nightmares (0.52).-t -Equates melanoma with death (0.39).$ -Thinks ‘I might die’ (0.57).* -Disturbed work function (0.68).* -Disturbed personal wellbeing (0.74).* -Disturbed family/social life (0.60).* -Feels as if ‘the bottom has fallen out of everything’ (0.65).§ -Thinks it was hard to adjust to melanoma (0.76).§ -Felt shock at learning diagnosis (0.59).§

2. Coping by avoidance: copes by action, by avoiding emotional discussions.

0.51

-Tries to keep busy with other things (0.65).* --Isn’t able to talk with family or friends about (0.51).$

3. Coping by changing: changing attitudes, relationships, temporal perspective as a result of having melanoma.

0.67

-Focused more on present (0.46).$ -Changed relationships, e.g., closer to family (0.45).* -Changed attitude to take more care of self, e.g., to eat better (0.45).$

4. Coping by denial: doesn’t want to think, know, or talk about melanoma.

0.62

-Tries not to think about it (0.43).+ -Doesn’t want to hear or talk about it (0.36).§ -Agrees that ‘what I don’t know won’t hurt me’ (0.41).$

5. Coping by optimism: seeing the brighter side of this experience.

0.64

-Thinks that getting melanoma was a turnaround/time of growth (0.44).$ -Thinks things have fallen into place/what’s important is clear (0.53).§ -Thinks of self as optimistic (0.33).$ -Tends to think positively (0.21).5

6. Coping with Strength: copes by trying hard to be positive, strong and stable.

0.43

-Makes an effort to think positively (0.21).5 -Has to know everything, no matter how hard the facts (0.27).§ -Considered capable of handling things/stable (0.46).§

7. Emotionally

0.90

-Subject’s reported feelings when first told diagnosis: shock (0.72), surprise (0.75), fear (0.78), anxiety (0.81), sadness (0.59); (each emotion rated separately). -Subject’s feelings expressed at time of interview: fear (0.72), anxiety (0.65), sadness (0.57); (each emotion rated separately).

8. Faith: placing faith in external authorities: God and/or physicians.

0.78

-Agrees ‘prayer can work miracles’ (0.58).§ -Agrees ‘I’m placing my faith in god’ (0.73).$ -Agrees ‘I’m placing my faith in my doctors’ (0.46).$

9. Minimizes: minimizes the seriousness of melanoma, in general, or of own condition.

0.96

-Patient minimizes general (0.92).* -Patient minimizes (0.92).*

Expressive:

it

seriousness

of melanoma,

in

seriousness

of own condition

144

Scale name and description

L. TEMOSHOK

Coefficient

alpha

etal.

Items composing

scale

-Down vs. up (0.58). -Emotionally constricted vs. labile (0.55). -Slow vs. fast (0.75). -Patient vs. impatient (0.63). -Lethargic vs. hurried (0.76). -Passive vs. active (0.85). -Sad vs. angry (0.66). -Bland vs. intense (0.78). -Given up vs. struggling (0.73). -Helpless vs. in control (0.55). -Hopeless vs. pursues opportunities world offers (0.65). -Smooth vs. jerky (0.24). -Appeasing vs. hostile (0.29). -Accepting vs. controlling (0.30). -Sincere vs. guarded (0.33). -Fluid vs. awkward (0.61). -Withdrawn vs. extended (0.63). -Number of times divorced, separated, or ended relationships during last 5 yr (0.78).-j-Number of major moves during last 5 yr (0.41).-t -Number of major changes in personal life during last 5 yr (0.61).t -Seriousness of loss of income or financial setback (0.28).*

10. Nonverbal Type C: mean rating of subjects as more Type C than Type A on 17 descriptive dimensions. /1,j--f

0.91

11. Stressful Changes: total number of relationship endings, financial loss, major moves, and major changes in personal life during the last 5 yr

0.67

12. Type A: rated more ‘Type A’ on the basis of responses to a brief version of the standardized interview developed to classify subjects as Type A or B (55).tt

0.62

-Irritation as waiting in lines (0.38). ( -Irritated by a slow driver when in traffic (0.25).7 -Anger is often directed outward rather than inward (0.52).1 -Subject feels a great deal of pressure/responsibility in job (0.35). 7 -Subject gets angry more than once a week (0.43). ?

13. Type C: rated more ‘Type C’ responses to questions regarding coping with demanding or powerful others; i.e., tries to please others, avoid conflict, not express negative feelings.**,tt

0.81

-When someone makes too demands on you, what do you typically do? (0.66).* -When someone who is more powerful than you are, such as a supervisor, tells you to do something you don’t think is right, what do you typically do? (0.60).*

*Rated from subject’s self-report during interview on a l-5 scale from ‘not at all’ to ‘strongly/greatly’. tActual number. *Rated from subject’s self-report during interview as yes/no (present/absent). §Rated from subject’s self-report during interview on a l-5 scale from ‘strongly agree’ to ‘strongly disagree’. //Based on coder’s rating of whole videotape interview on semantic differential scales (l-7), half of which were posed on the rating sheet with the hypothetical Type A direction high and half with the hypothetical Type C direction high. (Coder’s rating of subject on l-5 scale from strongly Type A to strongly Type B. **Coder’s rating of subject as strongly ‘Type C’ to not at all ‘Type C’ on 1-S behaviorally-anchored coding scheme derived by first author. ttln support of the theoretical rationale proposed in the introduction for a bipolar Type A-Type C dimension is the finding of a negative, significant correlation between the scales Type A and Type C (-0.3 1, p < 0.02). and between the scales Type A and Nonverbal Type C (-0.25, p < 0.06).

Psychosocial TABLE

II.-VARIABLES

factors

and melanoma

SIGNIFICANTLY

OR

NEARLY

HISTOPATHOLOCXC

Domains

prognostic

and variables

indicators

SIGNIFICANTLY

145

ASSOCIATED

Histopathologic Thickness

(in mm)

measures

*p
(I-5)

Level

r Medical risk and demographic: ‘At risk’ skin and eye coloring Age Occupational status Behavioral: Delay (time in months) Psychosocial: Faiths Nonverbal Type C§ Histrionic character style Narcissistic character style Situational: Less previous knowledge of melanot ma Less understanding of treatment

WITH

MEASURES

r

(57) (51)

-0.17 0.18 0.29t

(48) (49) (46)

0.24*

(49)

0.25*

(42)

0.32f 0.28t -0.31t -0.33t

(55) (55) (39) (39)

0.28t 0.32t

(49) (44)

-0.28t 0.21 0.11

(56)

0.22 0.15 -0.28 -0.36t 0.301 0.31t

(47) (47) (32) (32) (44) (40)

r= Pearson product moment r Numbers in parentheses refer to n for that variable Wtandardised scales (Z transformations)

RESULTS

Correlations with histopathologic measures The significant and near-significant correlations amongst medical risk, and situational factors with the two prognostic demographic, psychosocial, indicators (thickness and level) are depicted in Table II. Medical risk and demographic factors. In terms of medical risk and demographic variables ‘at risk’ complexion was significantly negatively correlated with tumor thickness. Less skilled occupational status was significantly correlated with level only. Delay behavior. Patient delay (number of months) in seeking medical attention for a suspicious lesion is moderately correlated with thickness and with anatomic level of invasion. Psychosocial variables. In terms of psychosocial variables, higher scores on ‘Nonverbal Type C’, and ‘Faith’ were significantly correlated with thicker lesions. ‘Nonverbal Type C’ is the rater’s assessment of the videotaped interview on 17 semantic differential scales of relative ‘Type A’ (e.g., active, impatient, in control) versus ‘Type C’ (e.g., passive, bland, appeasing, helpless) characteristics. ‘Faith’ refers to believing that prayer can work miracles, and that it is important to place one’s faith in God and the doctors. Of the self report measures, only Histrionic and Narcissistic character styles, from the Character Style Inventory, were significantly (negatively) correlated with tumor thickness. Knowledge of melanoma and its treatment. As a situational variable, less previous knowledge of melanoma (rated by coders on the following 4-point scale: ‘knew nothing about it, knew a little, knew the definition and had read about it, and knew someone who had the disease’) was associated with thicker and more invasive lesions. Similarly, less understanding of medical treatment for melanoma (rated by

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coders on a Spoint scale from no to full understanding) was significantly correlated with both histopathologic measures. Intercorrelations and semi-partial correlation analyses. A problem in directly interpreting the correlations presented in Table II is that while certain variables may be highly correlated with the histopathologic measures, these high correlations may be, in part, accounted for by other, covarying independent variables. In such cases, it is important to establish the amount of variance contributed by each independent variable, after covarying, independent variables are considered in the equation. TABLE III.-INTER-CORRELATIONS At-risk Coloring Age Occupational Status Delay Faith Nonverbal Type C Histronic Style Narcissistic

Age

occ. Status

OF VARIABLESFROM TABLE II Delay

Faith

Nonverb. Type C

Hist. Style

Nar. Style

Less Knowl. ___~

-0.12 -0.07 -0.04 -0.17

0.07 -0.001 0.21

-0.7 0.31*

0.05

-0.17

0.08

0.13*

-0.03

0.006

-0.38*

0.27

0.007

0.19

0.12

Style Less previous

0.08

-0.35*

-0.25

-0.31*

-0.10

-0.13

Knowledge/MM Less understanding of treatment

0.007

0.09

0.10

0.19

0.03

0.07

-0.13

-0.11

0.34*

0.33*

0.07

0.45?

0.54*

-0.27

-0.41*

-0.16

0.34t

-0.38*

0.47f

*p < 0.05 tP < 0.01 *p < 0.001

Table III shows the intercorrelations of the independent variables that were significantly or nearly significantly associated with the dependent variables, thickness and level. Of particular concern for interpretation of the relationship of psychosocial variables to tumor thickness are the significant correlations of two demographic variables-age and occupational status-with four psychosocial variables. Table IV presents semi-partial correlation analyses [71] between the four psychosocial variables and thickness, controlling for age or occupational status, and then the reciprocal. This table indicates that in every instance, it is the psychosocial variable that retains a significant or near-significant relationship with tumor thickness when the potentially confounding demographic variable is controlled for, while the reverse does not hold true. Table III also shows that four psychosocial variables are significantly associated with the situational variable, Less Understanding of Treatment for Malignant Melanoma (MM). Table V presents semi-partial correlations between this variable and tumor thickness, controlling for each significantly correlated other psychosocial variable, and vice-versa. These results indicate that the variables Less Understanding of Treatment, Faith, and Less Previous Knowledge are modestly correlated, independently of each other, with tumor thickness.

Psychosocial TABLE

factors

IV.-SEMI-PARTIAL PSYCHOSOCIAL

Independent

variable

and melanoma

status

Nonverbal Type C Occupational status Histrionic

style

Age Narcissistic Age

style

indicators

CORRELATIONS:

DEMOGRAPHIC

VARIABLES

TUMOR

Control

WITH

variable

__.__~_ Faith Occupational

prognostic

Occupational Faith

VARIABLES

147 AND

THICKNESS

Correlation with dependent variable tumor thickness

n

status

0.32T 0.11

51

Occupational status Nonverbal Type C

0.35T 0.1 I

51

Age Histrionic style

-0.27* 0.05

39

Age

-0.30* 0.15

39

Narcissistic

style

Less understanding of treatment Occupational status

Occupational status Less understanding

0.33T 0.16

41

Less understanding Age

Age Less understanding

0.32T 0.22

44

Faith Age

0.11 0.28’

54

Nonverbal Type C Age

0.16 0.27*

54

Age Faith Age Nonverbal

Type C

*p < 0.10. t p < 0.05. Note: Discrepancies in size of correlations between variables in this table and the same variables in Table II are attributable to differences in n when only the cases with no missing data for both variables are included in Table IV. Multiple regression analyses. A hierarchical multiple regression analysis was computed using seven variables significantly correlated with tumor thickness in Table II (Histrionic and Narcissistic Character Styles were not included because more data were missing on these variables than for the others). The rationale for the hierarchy was to enter first those variables with a presumed biological contribution to tumor thickness (‘At risk’ Complexion, and Age); then variables whose relation to thickness is most likely mediated by situational/behavioral factors (Delay, Previous Knowledge, and Understanding of Treatment); and finally variables for which linking mechanisms to tumor thickness are unknown (Faith and Nonverbal Type C). Tumor thickness was significantly predicted (negatively) by ‘At risk’ Complexion (F [1,25] =6.12, p < 0.03), and especially by Delay, (F [1,25] = 17.58, p < 0.0005). None of the other variables was significant. Combined R2 for the model (all 7 variables) was 0.60. Age interactions. Following suggestions in the literature [5,41,60,61], the sample was dichotomized into subjects less than age 55 or 55 yr and over. Correlations for the variables significantly associated with tumor thickness for all subjects (see Table II) were conducted separately for the two groups, between these variables and histopathologic indicators, as shown in Table VI.

148

L. TEMosHoK et al. TABLE

V.--SEMI-PARTIAL

CORRELATIONS

PSYCHOSOCIAL Independent

variable

OF

VARIABLES

Control

SIGNIFICANTLY WITH

variable

INTER-CORRELATED

THICKNESS Semi-partial of

correlations

independent

with

dependent tumor

Faith

Less

understanding

n

variable variable

thickness

Faith

0.20 0.20

44

Nonverbal

Type C Less understanding

Less understanding Nonverbal Type C

0.09 0.22

44

Narcissistic style Less understanding

Less understanding Narcissistic style

-0.07 0.36t

31

Less previous knowledge Less understanding

Less understanding Less previous knowledge

0.12 0.23

41

0.25* 0.19

54

Less

understanding

Faith Nonverbal

Type C

Nonverbal Type C Faith

*p < 0.10. f p < 0.05. Note: See note on Table IV

TABLE

VI.-THE

RELATIONSHIP

OF AGE TO PSYCHOSOCIAL

VARIABLES

Age < 55

FROM TABLE

II

Age > 55

Variables: Level

Thickness Faith Nonverbal Type C Histrionic style Narcissistic style Less knowledge/MM Less understanding/treat. Delay

0.41* 0.40$ -0.19 -0.27 0.26 0.42t 0.44%

(37) (37) (26) (26) (35) (29) (33)

0.39rf: 0.27 -0.19 -0.28 0.19 0.32* 0.31”

Thickness (33) (33) (22) (22) (33) (27) (30)

0.08 -0.04 -0.61+ -0.53* 0.29 0.01 0.02

(18) (18) (13) (13) (14) (15) (16)

Level -0.14 -0.08 -0.43 -0.47 0.61* 0.21 0.16

(14) (14) (10) (10) (11) (13) (12)

*p < 0.10 tp < 0.05 $p < 0.02 As hypothesized, all but three variables that were significantly associated with prognostic indicators in Table II were even more strongly correlated with these indicators within the younger age group. DISCUSSION

In contrast to other studies that have examined the relationship of demographic, biological, and/or psychosocial factors to (a) cancer incidence, or (b) disease progression, this study was concerned with factors related to prognostic indicators. For malignant melanoma, the best prognostic indicators are !wo histopathologic factors, tumor thickness and level of invasion in the skin.

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Darker coloring The perspective on disease severity as estimated by prognostic indicators should be emphasized in interpreting this study’s results relating unfavorable prognostic indicators with darker complexion. While light skin/eye/hair pigmentation may be a risk factor in disease initiation, disease severity as reflected in unfavorable prognostic indicators was associated in the present study with the opposite configuation of attributes. One possible interpretation for this unexpected finding is that melanoma lesions would be less noticeable against darker skin, and thus would have more time to grow before being diagnosed. Noticeability of a lesion is different from patient delay in seeking medical attention after noting a suspicious symptom; delay itself was not correlated with darker coloring. A related explanation is that because darker complected individuals are not thought to be at risk for developing malignant melanoma, they are not as vigilant nor as suspicious as lighter-skinned individuals about changes in their skin. They may also get more sun exposure, which is thought to be another melanoma risk factor.

Delay and related variables The results of the present study which found a positive, significant relationship between delay and unfavorable prognostic indicators are in contrast to the findings of Cassileth et al. [53], who found no such relationship. Another study by our group [34] posed some methodological explanations for this discrepancy, based on the need to differentiate subtypes of malignant melanoma, and the need to delete from the analysis behaviors that cannot be strictly defined as delaying seeking medical attention. An additional methodological argument is as follows: Thirty-six percent of the patients in the Cassileth study had delays of over two years (Dr. Cassileth, personal communication to L.T.), in sharp contrast to the present study in which only one patient had a delay of over two years. For some of their patients, it appears that delay was measured from the time when a mole was noted, rather than when a lesion was thought to be suspicious, as was the case for the present study. A mole may have been present for many years or even since birth, but the changes in it that signify malignancy may be recent. ‘Delay’ is more accurately defined as inaction after noticing a suspicious symptom or change in a lesion, than in terms of noting a mole that may or may not have changed. A significant correlation between delay and tumor thickness would be attenuated by several instances of delays over two years. Less previous knowledge of melanoma and less understanding of its treatment were significantly correlated with both tumor thickness and level of invasion. As in the case of patient delay, it is reasonable to assume that these variables and their underlying constructs, although assessed retrospectively (i.e., after diagnosis of melanoma), existed as states prior to diagnosis, and thus may have had some influence on tumor thickness and level of invasion. While it might be equally logical to assume that less previous knowledge and less understanding of treatment would be related to patient delay-which would give tumors an opportunity to grow thicker and deeper-delay is not significantly correlated with those two experiential variables. (However, another study by our group [34] which included a larger sample of n = 106 found that significantly longer delays characterised patients with less versus more previous knowledge.)

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The results of the hierarchical multiple regression analysis, which found delay to be the variable most significantly associated with tumor thickness as a dependent variable, suggest that interventions at the situational or behavioral level may be a relatively direct way to affect tumor thickness. For example, if patients are encouraged to seek medical attention sooner after noticing something suspicious, their primary melanoma lesions may be able to be treated at an earlier, prognostitally more favorable point. It should be emphasized, however, that the results of the hierarchical regression analysis do not clarify causality of tumor thickness. For example, it may be the case that certain psychological variables influence delay, which in turn affects tumor thickness. Alternatively, psychological variables may be linked to tumor thickness by entirely different mediating mechanisms in the realm of, for example, psychoneurodocrinology or psychoimmunology.

Psychosocial factors The findings on psychosocial factors related to prognostic indicators offer some insight into why there have been contradictory, inconclusive, and negative findings in the literature on psychosocial oncology. First, the relationships among variables are complex. Age, for example, showed hypothesized strong interactions with psychosocial variables in the present study. Correlations of psychosocial with prognostic factors were, with few exceptions, much stronger for subjects less than 55 yr of age. These findings are consistent with the notion that environmental factors and age-related deterioration of immune system functioning may play a larger role relative to psychosocial factors in older patients. Several psychosocial variables were strongly and significantly correlated with the variable of less understanding of treatment. These variables, which are part of the hypothetical ‘Type C’ constellation, are also significantly associated with tumor thickness. They appear to be related to tumor thickness independently of age or occupational status (with which they are also correlated), and partly independently of less understanding of treatment. While less understanding of treatment cannot be construed as a consequence of tumor thickness or level of invasion, an argument could be made [cf., 91 that the psychosocial variables found to be significantly correlated with thickness are reactions to having more prognostically unfavorable lesions. This argument is more applicable, however, to studies of cancer and noncancer controls, in which having cancer probably creates a very different psychological state than not having cancer. In the present study, all subjects had malignant melanoma. At the time of the interview, few patients had been told the thickness or level of invasion of their tumors (if in fact this was even known at that time), although they did have impressions about the relative severity of their conditions. It is unlikely that patient’s awareness and understanding of differences in millimeters of tumor thickness would, in and of itself, engender the significant associations found between psychosocial factors and prognostic indicators. The weight of clinical as well as research evidence is that when people are diagnosed with a disease, they do not suddenly change their usual ways of coping with stress or develop entirely new patterns. Thus, it is more probable that pre-existing and characteristic coping styles were mobilized for all patients by the stress of having malignant melanoma and of dealing with its treatment. The results of this study do not address the question of whether such stylistic tendencies played

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any role in the development of malignant melanoma, although they are consistent with studies on psychosocial factors associated with cancer progression and initiation [e.g., 15-281. Reflecting on the results of this study in light of the Type C constellation proposed by Temoshok and Heller [54], we see characteristics associated with thicker, more invasive tumors as (a) attitudinally Type C in the sense of placing faith in external authority, and (b) emotionally and behaviorally Type C in the sense of representing one end of bipolar dimensions opposite Type A emotional and behavioral tendencies. CONCLUSIONS

Amorig a series of demographic, physical risk, psychosocial, and stress factors, patient delay in seeking medical attention for suspicious lesions was found to contribute the most variance to tumor thickness, the best prognostic indicator for malignant melanoma. Separate from delay behavior, several psychosocial factors which are conceived of as part of a theoretical Type C constellation, are also significantly positively correlated with tumor thickness. It was not the aim of the present study to demonstrate the mechanisms by which such a psychosocial configuration might contribute to tumor thickness; however, the study provides a foundation for such future research. Acknowledgements-An

earlier version of this paper was read, in part, before the 89th Annual Convention of the American Psychological Association, Los Angeles, August 25, 1981. This research was supported in part by a University of California San Francisco Academic Senate Research Grant, and by a Biomedical Research Support Grant through the U.C.S.F. Department of Psychiatry, both to the first author, and National Cancer Institute grant No. 5301CA26655 to Dr. Blois. Dr. Martin Kamp, Director of the U.C.S.F. Computer Center, and the Environmental Epidemiology Branch of the National Cancer Institute generously provided partial support for the data analyses. We wish to thank Dr. Lynn E. Spitler, Director of the Melanoma Clinic at Children’s Hospital, San Francisco, for her consistent support and cooperation. Appreciation is due to Ms. Judy Curtiss for her valuable contributions to the coding of the videotaped interviews and to Ms. Sharon Singleton and Ms. Jeanne Barrett for preparing the manuscript. We are especially indebted to the patients who participated in our research.

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