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Study |

Impact of Melanoma on Patients' Lives Among 562 Survivors:  A Dutch Population-Based Study FREE

Cynthia Holterhues, MD; Darren Cornish, MD; Lonneke Veronique van de Poll-Franse, PhD; Gertruud Krekels, MD, PhD; Frans Koedijk, MD; Danielle Kuijpers, MD, PhD; Jan Willem Coebergh, MD, PhD; Tamar Nijsten, MD, PhD
[+] Author Affiliations

Author Affiliations: Departments of Dermatology (Drs Holterhues, Cornish, and Nijsten) and Public Health (Dr Coebergh), Erasmus MC, Rotterdam, the Netherlands; Comprehensive Cancer Centre South, Eindhoven, the Netherlands (Drs van de Poll-Franse and Coebergh); Center of Research on Psychology in Somatic Diseases (CoRPS), Tilburg University, Tilburg, the Netherlands (Dr van de Poll-Franse); Department of Dermatology, Catharina Hospital, Eindhoven (Dr Krekels); Department of Dermatology, St Elisabeth Hospital, Tilburg (Dr Koedijk); and Department of Dermatology, Amphia Hospital, Breda, the Netherlands (Drs Kuijpers and Nijsten).


Arch Dermatol. 2011;147(2):177-185. doi:10.1001/archdermatol.2010.433.
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Published online

Objective  To assess the impact of melanoma on the health-related quality of life of patients from the general population up to 10 years after diagnosis and its determinants.

Design  A cross-sectional Dutch population-based postal survey among patients with melanoma for the years 1998 to 2008 using the Eindhoven Cancer Registry.

Main Outcome Measures  The 36-Item Short-Form Health Survey (SF-36), Impact of Cancer (IOC) questionnaire and specific melanoma-related questions. The SF-36 scores of the cases were compared with normative data. Multiple linear regression models were used to identify associated factors of SF-36 and IOC scores.

Results  The response rate was 80%. The mean age of the 562 respondents was 57.3 years; 62% were female, and 76% had a melanoma with a Breslow thickness of less than 2 mm. The SF-36 component scores of patients with melanoma were similar to those of the normative population. In a multiple linear regression model, stage at diagnosis, female sex, age, and comorbidity were significantly associated (P < .05) with the physical and mental component scores. Women were significantly more likely to report higher levels of both positive and negative IOC. Time since diagnosis, tumor stage, and comorbidity were significant predictors of negative IOC scores. Women seemed to adjust their sun behavior more often (54% vs 67%; P < .001) than men and were more worried about the deleterious effects of UV radiation (45% vs 66%; P < .001).

Conclusion  The impact of melanoma seems to be specific and more substantial in women, suggesting that they may need additional care to cope with their melanoma optimally.

Figures in this Article

Although the prognosis is relatively good for about 80% of patients with melanoma, they remain at risk for disease progression and have an increased risk of developing subsequent melanomas.16 A systematic review on the impact of melanoma on patients' lives that included a variety of psychometric measures suggested that a third of patients with melanoma have reported clinically significant levels of distress.7 Therefore, melanoma can be considered a chronic life-threatening disease that may affect patients' lives considerably. Because most patients are aware that past sun exposure might have played a role in the development of their melanoma,8 they are likely to change their lifestyle to minimize UV exposure, which consequently may affect patients' health-related quality of life (HRQoL) as well.

The HRQoL impact of melanoma is not very well documented.7 Of the 13 eligible studies included in a systematic review, most included a relatively small number of patients who were almost always treated in specialized centers and assessed impact within 2 years after diagnosis. They used a variety of questionnaires assessing patient reported outcomes. Furthermore, a comparison of HRQoL impairment was not made between men and women and between patients with melanoma and the general population and/or other cancer groups.7 Although the Functional Assessment of Cancer Therapy–Melanoma (FACT-Melanoma) and the Skin Cancer Index have been introduced, neither of them is well suited to measure melanoma-specific HRQoL among the general population of melanoma survivors.7,911 The FACT-Melanoma was developed for clinical trial purposes that include high-risk patients who have lower survival rates than most patients with melanoma in the general population and who receive additional surgical and/or systemic therapy. The Skin Cancer Index was designed for keratinocytic cancers and not for melanoma.

The objective of this cross-sectional survey was to investigate the impact of melanoma on patients' HRQoL up to 10 years after diagnosis and the association between HRQoL impairment and patient and tumor characteristics. We hypothesized that melanoma survivors would report an impaired HRQoL compared with that of the normative Dutch population and that this impact would diminish over time and differ across sex. A generic and cancer-specific instrument and additional melanoma-specific items were used to evaluate HRQoL and associated factors in a large cohort of (long-term) melanoma survivors from the general Dutch population.

SETTING AND PARTICIPANTS

A cross-sectional survey was conducted with the assistance of the Eindhoven Cancer Registry (ECR), Eindhoven, the Netherlands. The ECR records data of patients newly diagnosed as having cancer in the southeast part of the Netherlands,12 which has a population of about 2.3 million inhabitants and is served by 18 hospital locations and 2 large radiotherapy institutions. Of the 18 hospitals, 3 large regional hospitals were asked to participate. From the ECR database, all patients diagnosed as having melanoma (International Classification of Diseases, Oncology, codes C44.0-C44.9 with morphology codes 8720-8790) from January 1, 1998, to August 1, 2007, in 1 of the 3 hospitals were identified. The time since diagnosis ranged from 6 months to a maximum of 10 years, owing to the fact that there is a 6-month delay before tumors are completely registered in the ECR.

Patients older than 85 years at the time of the survey were excluded because it was expected that they would have difficulty completing a self-administered questionnaire. Deceased patients were excluded by linking the database to the Central Bureau for Genealogy, which collects data on all deceased Dutch citizens or permanent residents via civil municipal registries.

The treating physicians of the 3 hospitals informed their eligible patients by sending a standardized invitation letter and the questionnaire. Patients were reassured that nonparticipation would not have consequences for their follow-up or treatment. By returning a completed questionnaire, patients consented to linkage of the HRQoL data with those of their disease and treatment history as registered in the ECR. Questionnaires were coded for anonymous data collection tracking and linkage with the ECR database. Data were collected from February through May 2008. The medical ethics committee of Catharina Hospital in Eindhoven gave their approval to this study.

STUDY OUTCOMES

The ECR provided data on melanoma and demographic characteristics of the patients. The questionnaire included a generic and cancer-specific HRQoL instrument (36-Item Short-Form Health Survey [SF-36] and Impact of Cancer [IOC], respectively) and additional questions regarding demographic variables, disease progression, and current comorbidity (adapted from the Charlson comorbidity index).1315 For the SF-36, standard scoring procedures of the 8 scales) (ie, Physical Functioning, Role Physical, Bodily Pain, General Health, Vitality, Social Functioning, Role Emotional subscale, Mental Health) were followed where higher scores indicate better functioning (range, 0-100).13 Two higher-order component scores for physical (PCS) and mental health (MCS) were also calculated. The IOC was developed by Zebrack et al15 in 2006 to measure the well-being of long-term cancer survivors and their adjustment to changes. It consists of 41 questions (5-point response scale), 6 domains (ie, physical, psychological, social, existential, meaning of cancer, health worry) with 10 dimensional subscales.14,15 These 10 subscales are Physical: Health Awareness (4 items); Physical: Body Changes (5 items); Psychological: Positive Self-Evaluation (8 items); Psychological: Negative Self-Evaluation (4 items); Existential: Positive Outlook (3 items); Existential: Negative Outlook (4 items); Social: Life Interferences (3 items); Social: Value of Relationships (2 items); Meaning of Cancer (5 items); and Health Worry (3 items). These subscales were combined to form a higher-order positive or higher-order negative scale (range, 0-5) with higher scores indicating a more positive or negative impact of cancer, respectively (Table 1). In addition to these preexisting validated instruments, several melanoma-specific items that assess issues related to treatment, impact on daily life, and follow-up were included (based on expert opinion) because these issues were not covered by the SF-36 or IOC questionnaires (see the subsections titled “Melanoma-Specific Items” and Practical Issues Related to Melanoma” in the “Results” section). Responses were categorized as “less,” “the same,” “a little bit more,” “more,” or “a lot more.” In the analyses, “more” and “a lot more” were combined. To evaluate the physical symptoms experienced due to melanoma or its treatment, questions regarding pain, itch, swelling, and numbness with a 3-point scale were included.9 Several items pertained to the extent to which the diagnosis of melanoma affected patients' sun (exposure) behavior (ie, activity in the sun, worry about the effects of the sun on the skin, and sun-protective measures) were included. Furthermore, patients were asked whether applications for health, life, and disability insurance or home mortgage had been hampered because of their melanoma.

Table Graphic Jump LocationTable 1 Domains and Subscales of the Impact of Cancer (IOC) and Their Coveragea
STATISTICAL ANALYSIS

To test for statistical differences, the t test and χ2 test for continuous and categorical variables, respectively, were used. The scores of the SF-36 scales were compared with an age- and sex-matched random normative sample of 1742 Dutch adults from the general population by means of analysis of variance.13 The age- and sex-matched sample was drawn from a nationwide sample of the Dutch adults to whom the SF-36 was mailed (2800 households drawn at random from the national telephone registry). Nonresponders were sent reminder letters after 2 months and 3 months following initial mailing. In total, 1771 were returned, representing a 63% response rate, of whom 56% was male.13 We used Norman's “rule of thumb,”16 which says that the threshold of discrimination for changes in HRQoL for chronic diseases seems to be approximately half a standard deviation.

Multivariate linear regression analyses were performed to estimate the association between SF-36 and IOC scores and independent variables (expressed as standardized β-coefficients and 95% confidence intervals). Variables were included in the multivariate model if they were significantly associated with the outcome in the univariate analysis and/or were considered a priori to be of clinical relevance. In these models, age and time since diagnosis were entered as continuous variables, tumor stage ranged from I to IV, and presence of comorbidity was binary (yes/no). Four levels of education were used, and marital status was categorized as having a partner vs no partner.

A 2-sided P <.05 was considered statistically significant. All statistical analyses were performed using SAS statistical software (version 9.1 for Windows; SAS Institute Inc, Cary, North Carolina).

STUDY POPULATION

Of the 992 patients diagnosed as having cutaneous melanoma in 1 of 3 hospitals between January 1998 and August 2007, 802 patients were alive on August 1, 2007 (Figure 1). Of these patients, 103 could not be contacted (Figure 1). The remaining 699 survivors received a questionnaire, and 562 responded (a 80.4% response rate). The distribution of the demographic and melanoma characteristics of the respondents, nonrespondents, and patients with unverifiable addresses were similar with respect to sex, Breslow thickness, stage at diagnosis, and initial treatment (Table 2). Nonrespondents and patients with unverifiable addresses were generally younger (P < .05). On average, nonresponders also had longer survival times.

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Figure 1

Schematic flow diagram of ascertainment of the study population.

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Table Graphic Jump LocationTable 2 Sociodemographic and Clinical Characteristics of Questionnaire Respondents, Nonrespondents, and Patients With Unverifiable Addresses

About 70% of patients had been diagnosed as having stage I melanoma, and 49% had a lesion with a Breslow thickness of less than 1 mm (Table 2). Almost all patients underwent local surgical excision, and 20% underwent a sentinel node procedure (SNP). Chemotherapy or radiotherapy was administered in less than 1% of patients. No statistically significant differences were found for Breslow thickness (P = .64) and stage distribution (P = .71) between responders, nonresponders, and patients with unverifiable addresses.

The mean ages at diagnosis and at time of survey of the respondents were 52.6 years and 57.2 years, respectively. Sixty-two percent of respondents were female. Most respondents had at least a high school education, were married, had children, and were employed at time of survey (Table 3). Of all respondents, 35% reported at least 1 other medical condition: hypertension, joint complaints, and/or a history of a malignant disease.

Table Graphic Jump LocationTable 3 Sociodemographic and Clinical Characteristics of 562 Survivors (Respondents)
36-ITEM SHORT-FORM HEALTH SURVEY

Compared with an age- and sex-matched sample from the general Dutch population, melanoma survivors did not report impaired HRQoL as measured by the SF-36 (Figure 2). Interestingly, patients with melanoma scored statistically significantly higher on PCS and several subscales (Physical Functioning, Role Limitations: Emotional Problems, Mental Health, Bodily Pain, and General Health; data not shown) than the general population, but the mean score differences were less than half a standard deviation suggesting no clinical significant differences, according to Norman's rule of thumb (Figure 2).16

Place holder to copy figure label and caption
Figure 2

The 36-Item Short-Form Health Survey (SF-36) scores of patients with melanoma compared with normative population. BP indicates Bodily Pain; GH, General Health; MCS, Mental Component Scale; MH, Mental Health; PCS, Physical Component Scale; PF, Physical Functioning; RE, Role Emotional; RP, Role Physical; SF, Social Functioning; and VT, Vitality.

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After adjusting for age at time of the survey, years since diagnosis, disease stage, SNP, comorbidity, marital status, and educational level in a multivariate analysis, female sex, older age, tumor stage, and comorbidity were significantly negatively associated with PCS, whereas an SNP was positively associated (Table 4). Female sex and comorbidity were also negatively associated with MCS, whereas having a partner was positively associated with MCS. Women scored significantly lower (indicating higher HRQoL impairment) than men: 1.8 points (P < .05) on the PCS and 2.3 points (P < .05) on the MCS; however, this was not clinically relevant. In addition, female melanoma survivors reported higher impairment on 5 of 8 subscales (Physical Functioning, Bodily Pain, General Health, Vitality, and Mental Health; data not shown).

Table Graphic Jump LocationTable 4 β-Coefficients of Multiple Linear Regression Analysis: Investigating Factors Associated With SF-36 Component Scales and IOC Higher-Order Scales
IMPACT OF CANCER

To estimate the impact of melanoma on patients' psychological well-being in more detail, the IOC was included14 (Table 1). The mean scores of patients with melanoma for each subscale of the IOC differed from 2.2 to 3.1. The lowest scores were seen on the subscale Social: Life Interferences, which focuses on cancer- or treatment-related symptoms of the cancer that interferes with a patients' socializing, traveling, or time with family. The highest score of 3.1 was seen on the Existential: Positive Outlook subscale, which covers increased wisdom and spirituality due to the cancer experience.

In multivariate analyses, female sex was statistically significantly associated with higher-order positive and negative scales, suggesting that women experience both a more negative and more positive impact of melanoma on their psychological well-being than men (Table 4): compared with men, women scored 0.21 points (P < .05) higher on the higher-order positive scale and 0.24 points (P < .001) on the higher-order negative scale. Analyses showed that the trends of responses were similar, but that women responded more extremely compared with men (data not shown). On the higher-order negative scale, time since diagnosis was significantly associated with a negative β-coefficient, which implies that for every year further from diagnosis the patient may be less negatively influenced by their cancer. In contrast, more comorbidities and advanced melanoma stage (III vs I) were associated with a higher-order negative IOC score (Table 4).

MELANOMA-SPECIFIC ITEMS

Compared with men, a significant larger proportion of women reported going on vacation to sunny destinations less frequently (67% vs 56%, respectively; P = .03). Women were also more worried about the effects of sunlight on their skin (66% vs 45%; P < .001) and that of their spouses and children (49% vs 32%; P < .05).

Furthermore, female patients reported seeking shade and/or using sunscreen more often than men (67% vs 48%; P < .001) (Figure 3). Most men and women reported using sunscreen only in the summer or when the sun shines (83% vs 90%, respectively), with a sun protection factor of 20 to 30 or more (69% vs 72%, respectively). Women were more likely to use sunscreen more times a day than men (25% vs 64%; P < .001).

Place holder to copy figure label and caption
Figure 3

Men's and women's attitudes and behaviors since the diagnosis of melanoma. Responses to melanoma-specific items in men (A) and women (B). Melanoma-specific items questioned melanoma survivors about the extent to which they had changed their sun (exposure) behavior since the diagnosis of melanoma.

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Compared with men, women experienced more pain (26% vs 11%; P < .001), itchiness (26% vs 21%; P = .26), and numbness (29% vs 21%; P = .10) of their scars. Swelling of the scar or one of the extremities was reported in approximately 10% of men and women.

PRACTICAL ISSUES RELATED TO MELANOMA

Most survivors (94%) stated that their professional situation had not changed after being diagnosed as having melanoma. Five percent of survivors indicated that they had changed jobs, reduced the number of hours worked, had been retrained, or stopped working entirely (including work disability) as a result of their melanoma. Of the 258 patients who attempted to obtain health insurance in the survey period, 5% reported having experienced cancer-related problems in obtaining health insurance. Thirty-five percent (n = 84) reported difficulties obtaining life insurance, 15% (n = 98) reported problems with obtaining a mortgage, and 18% (n = 38) experienced trouble obtaining disability insurance when attempting to obtain one of these.

To our knowledge, this is the first study to investigate SF-36 and IOC scores in a population-based sample of melanoma survivors, showing relatively little impairment of the generic health status and HRQoL. In contrast to our hypothesis, the SF-36 scores were not significantly different compared with the normative SF-36 scores of the general Dutch population. This observation suggests that generic and even cancer-specific HRQoL questionnaires might not be sensitive enough for patients with predominantly low stages of melanoma. More specific, but individual, items showed that several UV-related aspects of patients' lives were affected and that having been diagnosed as having malignant melanoma had practical implications for their daily life (eg, getting a mortgage, health insurance, or life insurance).

Of the studied determinants, female sex was most strongly associated with HRQoL. Also, in the multivariate analyses of SF-36 and IOC scores, older age, comorbidity, and higher tumor stage were significant predictors for lower HRQoL.

We compared the SF-36 scores of patients with melanoma with normative data for the SF-36 obtained from of a nation-wide random sample of Dutch adults (see the “Methods” section), which have been used by several previous studies to compare the SF-36 scores of patients with those of the general population.17,18 Though not clinically relevant (statistical differences, <0.5 SD),16 the scores of several SF-36 domains and components were significantly higher among patients with melanoma than those from the general population.19,20 The finding that patients show far more variability in the response distribution of the individual melanoma-specific items (eg, sun behavior and worry) than in the generic SF-36 may confirm the need to combine generic with disease-specific questionnaires.19 Although it seems counterintuitive at first and in contrast with our hypothesis, this observation is in accordance with studies investigating other cancers showing that patients who had “survived” a cancer rate their generic HRQoL as similar or even better than those from the general population.12 Individuals can use various cognitive strategies such as belief, posttraumatic growth, or benefit finding to counteract the negative effect of illness (eg, melanoma) on their well-being.11 Finding benefit and growth could be viewed as part of the so-called response shift. When diagnosed as having a life-threatening disease, patients may change their internal standard of what constitutes health and HRQoL (recalibration), adjust their priorities (reprioritization), and/or redefine what is important to them (reconceptualization) in face of their condition.11,21

Of the variables studied in multivariate models, female sex was most strongly associated with lower SF-36 scores, higher-order negative and positive IOC scores, and more extreme responses to melanoma-specific items, which is confirmed by previous studies in melanoma and other cancers that show a sex difference in the assessment of HRQoL.7,11,22 In clinical practice, this observation may imply that women need additional care, including follow-up and possibly counseling to optimally cope with their melanoma.8 However, men might be less aware of general measures of sun protection and need education about these measures after treatment. Besides, other studies that used specific tools to measure anxiety and/or depression suggest that around a third of patients with melanoma suffer substantially.7 This could be reduced by psychological counseling, which might even lead to better survival.23 In addition to sex, comorbidity was strongly associated with HRQoL impairment due to melanoma. This association has been observed previously in patients with melanoma,7 nonmelanoma skin cancers,22 and solid cancers, suggesting that it remains difficult to differentiate the impact of different diseases. It seems that the impact of skin cancer is lowered by the presence of multiple or severe comorbidities. This observation emphasizes the need to test HRQoL instruments for item bias across the presence of comorbidity because an optimal HRQoL tool should not be influenced by external factors.19 The finding that older age at time of survey predicted lower scores on the physical scales is most likely explained by the presence of other disabilities and/or an aging effect of the cohort. In the long term, the effect of SNPs was reported as positive on the PCS, which is in agreement with other studies suggesting that additional therapy eventually increased HRQoL in patients with melanoma.24 The relatively small group of respondents who had an SNP reported a higher PCS score than those who did not, which is surprising, as surgical complications (eg, lymphoedema and extensive scarring) are likely to impair a patient's well-being. This may suggest that patients who choose to undergo additional or even controversial investigations and/or therapies may differ from those who received local surgical excision only. Although it was initially hypothesized, time since diagnosis did not affect SF-36 scores among melanoma survivors, and the effect of additional years after diagnosis was modest for the negative IOC scale. In other diseases, such as diabetes mellitus, rheumatoid arthritis, non-Hodgkin‘s lymphoma, and breast cancer, the effect of time since diagnosis on finding benefit or growth is inconsistent.11,17 The low adjusted R2 scores of the multivariate models that assessed predictors of SF-36 and IOC scores suggest that this analysis suffers from residual confounding (ie, multiple HRQoL predictors, such as anxiety, personality type, and coping mechanisms were not included in the analysis).7,13,14,25

Although the effect of melanoma on SF-36 and IOC scores seems to be limited, this cancer may have a profound impact on practical issues of patients' lives and thus affects HRQoL in different domains. A small proportion of individuals experienced difficulties in getting health insurance as a result of their melanoma, but up to a third of the patients experienced difficulty getting life insurance, disability insurance, and/or a mortgage. This type of information is not often assessed in patient populations but seems to be highly relevant in patients who have survived cancer.

This is the largest cross-sectional, population-based study using cancer registry data to investigate the impact of melanoma on patients' HRQoL and other aspects of their lives. Trask and Griffith22 investigated HRQoL among a large group of patients with melanoma ascertained from a multidisciplinary melanoma clinic. However, compared with our study, the design of their study22 was very different (eg, selected HRQoL measures, domain-specific tools, including anxiety and depression scales and categorization of patients), making a comparison between the study findings challenging.

A response rate of 80% is very high and in accordance with those of previous studies performed in the southeast part of the Netherlands.17,18 This high response rate and the fact that respondents and nonrespondents were comparable suggest that selection bias had a minimal effect on the results of this study. Because no specialized melanoma centers were included, the generalizability of our findings is likely to be good. The ECR is a well established cancer registry12 but does not record recurrence or metastasis from/after melanoma. Consequently, the effect of these events could not be studied separately. No information was available regarding the social economic status (SES) of patients. Higher levels of SES are associated with increased melanoma risk and higher HRQoL.2628 As a proxy for SES, educational level was used; three-quarters of the patients had at most a high school degree (Table 2), suggesting a possible overestimation of melanoma on HRQoL.

The SF-36 was used because it is the most commonly used HRQoL instrument and has the advantage of available Dutch norm data, but it is has not been formerly tested in patients with melanoma.19 To expand the focus of this study, the IOC, which is a relatively new instrument (and has not been validated in patients with melanoma) and several single items were added. At the time of the survey, the FACT-M, which was intended for the use in clinical trials with a focus on physical limitations, had not yet been validated.9,10 An indirect comparison of IOC scores suggests that patients' physical and psychological well-being is likely to be less affected by melanoma when compared with breast, prostate, colorectal, or prostate cancer. Patients with melanoma scored lower on all of the positive IOC subscales and higher on only 2 of the negative subscales (body changes and negative self- evaluation)15 (Table 1).

In conclusion, in a population-based sample of patients who have had malignant melanoma, the impact of melanoma seems to be fairly specific and is not driven by (long-term) treatment effects that affect generic or cancer-specific HRQoL. Therefore, there is need for a melanoma-specific HRQoL instrument that gauges the impact of thin and thick melanomas on patients' lives. Female sex and comorbidity were the main predictors of HRQoL impairment in patients with melanoma, but other (psychological) factors are likely to play a role as well and need to be studied in more detail in future studies.

Correspondence: Tamar Nijsten, MD, PhD, Department of Dermatology, Erasmus MC, Burg s’Jacobplein 51, Gk-316, 3000 CA Rotterdam, the Netherlands (t.nijsten@erasmusmc.nl).

Accepted for Publication: June 11, 2010.

Author Contributions: Drs Holterhues, Cornish, van de Poll-Franse, and Nijsten had full access to all of the data and take responsibility for the integrity of the data and accuracy of the data analysis. Study concept and design: Holterhues, Cornish, van de Poll-Franse, and Nijsten. Acquisition of data: Holterhues, Cornish, van de Poll-Franse, Krekels, Koedijk, and Kuijpers. Analysis and interpretation of data: Holterhues, Cornish, van de Poll-Franse, and Nijsten. Drafting of the manuscript: Holterhues, Cornish, van de Poll-Franse, and Nijsten. Critical revision of the manuscript for important intellectual content: Cornish, van de Poll-Franse, Krekels, Koedijk, Kuijpers, Coebergh, and Nijsten. Statistical analysis: Holterhues, Cornish, van de Poll-Franse, and Nijsten. Obtained funding: Nijsten. Administrative, technical, and material support: van de Poll-Franse, Krekels, Koedijk, Kuijpers, Nijsten, and Coebergh. Study supervision: van de Poll-Franse, Nijsten, and Coebergh.

Financial Disclosure: None reported.

Previous Presentation: An earlier version of these data was presented at the Fifth International Dermato-Epidemiology Association Congress; September 7, 2008; Nottingham, England (Abstract: Holterhues et al. Impact of melanoma on patients' lives: cross-sectional population-based study in the South Netherlands. J Invest Derm. 2008;128:2558).

Additional Contributions: The registry team of the Eindhoven Cancer Registry provided melanoma-specific data.

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Both  HEssink-Bot  MLBusschbach  JNijsten  T Critical review of generic and dermatology-specific health-related quality of life instruments. J Invest Dermatol 2007;127 (12) 2726- 2739
PubMed Link to Article
Ware  JE SF-36 Health Survey: Manual and Interpretation Guide.  Boston, MA: Health Institute, New England Medical Centre; 1993
Sprangers  MAde Regt  EBAndries  F Which chronic conditions are associated with better or poorer quality of life? J Clin Epidemiol 2000;53 (9) 895- 907
PubMed Link to Article
Trask  PCGriffith  KA The identification of empirically derived cancer patient subgroups using psychosocial variables. J Psychosom Res 2004;57 (3) 287- 295
PubMed Link to Article
Fawzy  FICanada  ALFawzy  NW Malignant melanoma: effects of a brief, structured psychiatric intervention on survival and recurrence at 10-year follow-up. Arch Gen Psychiatry 2003;60 (1) 100- 103
PubMed Link to Article
Chen  TBertenthal  DSahay  ASen  SChren  MM Predictors of skin-related quality of life after treatment of cutaneous basal cell carcinoma and squamous cell carcinoma. Arch Dermatol 2007;143 (11) 1386- 1392
PubMed Link to Article
Mols  FHolterhues  CNijsten  Tvan de Poll-Franse  LV Personality is associated with health status and impact of cancer among melanoma survivors. Eur J Cancer 2010;46 (3) 573- 580
PubMed Link to Article
van Hattem  SAarts  MJLouwman  WJ Increase in basal cell carcinoma incidence steepest in individuals with high socioeconomic status: results of a cancer registry study in The Netherlands. Br J Dermatol 2009;161 (4) 840- 845
PubMed Link to Article
Clegg  LXReichman  MEMiller  BA Impact of socioeconomic status on cancer incidence and stage at diagnosis: selected findings from the surveillance, epidemiology, and end results: National Longitudinal Mortality Study. Cancer Causes Control 2009;20 (4) 417- 435
PubMed Link to Article
Pappa  EKontodimopoulos  NPapadopoulos  AANiakas  D Assessing the socio-economic and demographic impact on health-related quality of life: evidence from Greece. Int J Public Health 2009;54 (4) 241- 249
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure 1

Schematic flow diagram of ascertainment of the study population.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 2

The 36-Item Short-Form Health Survey (SF-36) scores of patients with melanoma compared with normative population. BP indicates Bodily Pain; GH, General Health; MCS, Mental Component Scale; MH, Mental Health; PCS, Physical Component Scale; PF, Physical Functioning; RE, Role Emotional; RP, Role Physical; SF, Social Functioning; and VT, Vitality.

Graphic Jump Location
Place holder to copy figure label and caption
Figure 3

Men's and women's attitudes and behaviors since the diagnosis of melanoma. Responses to melanoma-specific items in men (A) and women (B). Melanoma-specific items questioned melanoma survivors about the extent to which they had changed their sun (exposure) behavior since the diagnosis of melanoma.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1 Domains and Subscales of the Impact of Cancer (IOC) and Their Coveragea
Table Graphic Jump LocationTable 2 Sociodemographic and Clinical Characteristics of Questionnaire Respondents, Nonrespondents, and Patients With Unverifiable Addresses
Table Graphic Jump LocationTable 3 Sociodemographic and Clinical Characteristics of 562 Survivors (Respondents)
Table Graphic Jump LocationTable 4 β-Coefficients of Multiple Linear Regression Analysis: Investigating Factors Associated With SF-36 Component Scales and IOC Higher-Order Scales

References

Coebergh  JWJanssen  MLouwman  M Cancer Incidence, Care and Survival in the South of the Netherlands, 1955-1999: a Report From the Eindhoven Cancer Registry With Cross-Border Implications.  Eindhoven, the Netherlands: Eindhoven Cancer Registry; 2001
de Vries  EBray  FICoebergh  JWParkin  DM Changing epidemiology of malignant cutaneous melanoma in Europe 1953-1997: rising trends in incidence and mortality but recent stabilizations in western Europe and decreases in Scandinavia. Int J Cancer 2003;107 (1) 119- 126
PubMed Link to Article
de Vries  ESchouten  LJVisser  OEggermont  AMCoebergh  JWWorking Group of Regional Cancer Registries, Rising trends in the incidence of and mortality from cutaneous melanoma in the Netherlands: a Northwest to Southeast gradient? Eur J Cancer 2003;39 (10) 1439- 1446
PubMed Link to Article
van der Rhee  HJvan der Spek-Keijser  LMvan Westering  RCoebergh  JW Increase in and stabilization of incidence and mortality of primary cutaneous malignant melanoma in Western Netherlands, 1980-95. Br J Dermatol 1999;140 (3) 463- 467
PubMed Link to Article
Johnson  TMHamilton  TLowe  L Multiple primary melanomas. J Am Acad Dermatol 1998;39 (3) 422- 427
PubMed Link to Article
Titus-Ernstoff  LPerry  AESpencer  SK Multiple primary melanoma: two-year results from a population-based study. Arch Dermatol 2006;142 (4) 433- 438
PubMed Link to Article
Cornish  DHolterhues  Cvan de Poll-Franse  LVCoebergh  JWNijsten  T A systematic review of health-related quality of life in cutaneous melanoma. Ann Oncol 2009;20(suppl 6)vi51- vi58
PubMed Link to Article
Francken  ABBastiaannet  EHoekstra  HJ Follow-up in patients with localised primary cutaneous melanoma. Lancet Oncol 2005;6 (8) 608- 621
PubMed Link to Article
Cormier  JNDavidson  LXing  YWebster  KCella  D Measuring quality of life in patients with melanoma: development of the FACT-Melanoma subscale. J Support Oncol 2005;3 (2) 139- 145
PubMed
Cormier  JNRoss  MIGershenwald  JE Prospective assessment of the reliability, validity, and sensitivity to change of the Functional Assessment of Cancer Therapy-Melanoma questionnaire. Cancer 2008;112 (10) 2249- 2257
PubMed Link to Article
de Ridder  DGeenen  RKuijer  Rvan Middendorp  H Psychological adjustment to chronic disease. Lancet 2008;372 (9634) 246- 255
PubMed Link to Article
Janssen-Heijnen  MLGLouwman  WJvan de Poll-Franse  LV Results of 50 Years Cancer Registry in the South of the Netherlands; 1955-2004.  Eindhoven, the Netherlands: Eindhoven Cancer Registry; 2005
Aaronson  NKMuller  MCohen  PD Translation, validation, and norming of the Dutch language version of the SF-36 Health Survey in community and chronic disease populations. J Clin Epidemiol 1998;51 (11) 1055- 1068
PubMed Link to Article
Gudbergsson  SBFosså  SDGanz  PAZebrack  BJDahl  AA The associations between living conditions, demography, and the ‘impact of cancer’ scale in tumor-free cancer survivors: a NOCWO study. Support Care Cancer 2007;15 (11) 1309- 1318
PubMed Link to Article
Zebrack  BJGanz  PABernaards  CAPetersen  LAbraham  L Assessing the impact of cancer: development of a new instrument for long-term survivors. Psychooncology 2006;15 (5) 407- 421
PubMed Link to Article
Norman  GRSloan  JAWyrwich  KW Interpretation of changes in health-related quality of life: the remarkable universality of half a standard deviation. Med Care 2003;41 (5) 582- 592
PubMed
Mols  FAaronson  NKVingerhoets  AJ Quality of life among long-term non-Hodgkin lymphoma survivors: a population-based study. Cancer 2007;109 (8) 1659- 1667
PubMed Link to Article
van de Poll-Franse  LVMols  FEssink-Bot  ML Impact of external beam adjuvant radiotherapy on health-related quality of life for long-term survivors of endometrial adenocarcinoma: a population-based study. Int J Radiat Oncol Biol Phys 2007;69 (1) 125- 132
PubMed Link to Article
Both  HEssink-Bot  MLBusschbach  JNijsten  T Critical review of generic and dermatology-specific health-related quality of life instruments. J Invest Dermatol 2007;127 (12) 2726- 2739
PubMed Link to Article
Ware  JE SF-36 Health Survey: Manual and Interpretation Guide.  Boston, MA: Health Institute, New England Medical Centre; 1993
Sprangers  MAde Regt  EBAndries  F Which chronic conditions are associated with better or poorer quality of life? J Clin Epidemiol 2000;53 (9) 895- 907
PubMed Link to Article
Trask  PCGriffith  KA The identification of empirically derived cancer patient subgroups using psychosocial variables. J Psychosom Res 2004;57 (3) 287- 295
PubMed Link to Article
Fawzy  FICanada  ALFawzy  NW Malignant melanoma: effects of a brief, structured psychiatric intervention on survival and recurrence at 10-year follow-up. Arch Gen Psychiatry 2003;60 (1) 100- 103
PubMed Link to Article
Chen  TBertenthal  DSahay  ASen  SChren  MM Predictors of skin-related quality of life after treatment of cutaneous basal cell carcinoma and squamous cell carcinoma. Arch Dermatol 2007;143 (11) 1386- 1392
PubMed Link to Article
Mols  FHolterhues  CNijsten  Tvan de Poll-Franse  LV Personality is associated with health status and impact of cancer among melanoma survivors. Eur J Cancer 2010;46 (3) 573- 580
PubMed Link to Article
van Hattem  SAarts  MJLouwman  WJ Increase in basal cell carcinoma incidence steepest in individuals with high socioeconomic status: results of a cancer registry study in The Netherlands. Br J Dermatol 2009;161 (4) 840- 845
PubMed Link to Article
Clegg  LXReichman  MEMiller  BA Impact of socioeconomic status on cancer incidence and stage at diagnosis: selected findings from the surveillance, epidemiology, and end results: National Longitudinal Mortality Study. Cancer Causes Control 2009;20 (4) 417- 435
PubMed Link to Article
Pappa  EKontodimopoulos  NPapadopoulos  AANiakas  D Assessing the socio-economic and demographic impact on health-related quality of life: evidence from Greece. Int J Public Health 2009;54 (4) 241- 249
PubMed Link to Article

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