Annals of Oncology Advance Access published online on March 19, 2008
Annals of Oncology, doi:10.1093/annonc/mdn064
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Quality of life and comorbidity score as prognostic determinants in non-small-cell lung cancer patients
1 Thoracic Oncology Unit, Centre Hospitalier Universitaire de Montpellier, Hôpital Arnaud de Villeneuve
2 Department of Statistics and Epidemiology, University Institute for Clinical Research, Université de Montpellier I, Montpellier, France
* Correspondence to: Dr J.-L. Pujol, Centre Hospitalier Universitaire de Montpellier Hôpital Arnaud de Villeneuve, F-34295 Montpellier Cedex 5, France. Fax: +33 4 67 33 61 36; Fax: +33 4 67 33 61 35; E-mail: jl-pujol{at}chu-montpellier.fr
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Abstract |
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 Top Abstract introductionpatients and methodsresultsdiscussionfundingappendixReferences |
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Background: Both quality of life (QoL) and comorbidity influence therapy and prognosis of non-small-cell lung cancer (NSCLC). We previously developed a lung cancer disease-specific simplified comorbidity score (SCS) and demonstrated the prognostic impact of this disease-specific instrument. This study aimed at validating the SCS in a prospective bicentric NSCLC population by measuring its relative prognostic determinant impact taking into account well-established variables such as QoL, performance status (PS), Charlson comorbidity index (CCI) and disease stage.
Patients and methods: Prognostic values of different pretherapeutic features were tested in univariate and multivariate analyses in a population of 301 NSCLC.
Results: Median survival was 17 months. One-third of patients reporting difficulties in their normal daily activities and an overall poor QoL. The following pretreament variables were independent determinants of a shorter overall survival: advanced disease, SCS, Lung Cancer Symptoms Scale global symptoms score, anaemia, hyponatremia, serum alkaline phosphatases level, serum CYFRA 21-1 and serum neuron-specific enolase.
Conclusion: In this extended validation population, the SCS is more informative than the CCI in predicting NSCLC patient outcome as the former is also more disease specific. Combination of both SCS comorbidity score and LSCC QoL yields a more accurate information that conventional analysis of PS.
comorbidities, non-small-cell lung cancer, prognosis, quality of life
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introduction |
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TopAbstractintroductionpatients and methodsresultsdiscussionfundingappendixReferences |
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The poor prognosis of advanced non-small-cell lung cancer (NSCLC) and the increase incidence of the disease in most of the developed countries urge the search for new therapeutic approaches. However, not all patients are eligible (or agree to participate) in research protocols. For these patients, the new guidelines for the treatment of NSCLC are considered as a handbook for daily care of patients suffering from advanced disease. Main disease characteristics taken into account by the guidelines algorithms are disease stage and Eastern Cooperative Oncology Group (ECOG) performance status (PS). However, other important patients' features such as comorbidities and pretherapeutic quality of life (QoL) might be important in defining groups of patients differing by their prognostic and determining patient-by-patient best therapeutic option.
Defining prognostic determinants of NSCLC may help physicians in decision making for both clinical trials and routine practice [1]. In routine practice, therapeutic decision might be influenced by the state of prognostic variables [1]. In the clinical trials setting, stratification of randomisation on known prognostic factors is an important part of procedure. Up till now, aside the aforementioned most widely accepted prognostic determinants, i.e. disease stage and PS [2], many large trials considered other features such as male gender, age older than 60 years, nonsquamous histologies, weight loss as stratification factors insofar as they have been reported as negative prognostic factors [3]. Accurate definition of NSCLC prognosis might require simultaneous appraisal of putative new determinants such as QoL and comorbidity score together with well-known aforementioned prognostic factors.
The term ‘comorbidity’ refers to noncancer-related physical and mental disorders that may also affect a patient outcome and treatment safety. Comorbidity should be distinguished from functional status, because the latter is a measure of a patient's ability to perform daily activities or other tasks [4]. In routine NSCLC care, comorbidities may preclude the physician from delivering optimal therapy because of possible treatment-related side-effect enhancement. Furthermore, for cancer occurring in the elderly, comorbidities could have a major impact on survival [5]. In lung cancer clinical trials, considering severe comorbidities as criterion for noneligibility enhances confidence that any observed differences between randomly assigned groups are attributable to therapy instead of confounding effect of unbalanced comorbid diseases. As a result, patients participating in lung cancer trials are likely to present with good general health criteria, whereas other patients affected by common comorbidity are referred to routine therapy. Consequently, clinical trials do not perfectly reflect patient characteristics from cohorts routinely treated in cancer units for an NSCLC.
In different human malignancies including lung cancer, the negative survival impact of comorbidities has been shown to be a prognostic determinant that is distinct from main disease characteristics (i.e. PS and tumour stage) [4, 6]. One can consider comorbidities as partly explaining discrepancies in patient outcome from one study to the other such as it has been observed in stage I NSCLC, varying from 43% to 84%.
Comorbid conditions have been evaluated using clinical scores in longitudinal studies. The most widely used clinical score is the Charlson comorbidity index (CCI) [7]. CCI has been constructed by analysing in a longitudinal study, 559 patients admitted in a single institution. Any disease or clinical condition inducing a 1-year relative risk of death >1.2 was included in the index. Nineteen conditions were found to significantly influence survival and were given a weighted value proportionally to their specific impact in relative mortality risk. The sum of the weighted scores of all the comorbid conditions present in patients was then scaled to establish the CCI. The weighted index was tested for its ability to predict mortality in a cohort of women with histologically proven primary breast cancer. With each increased level of CCI, there was a stepwise increase in the cumulative mortality attributable to comorbid disease.
In a previously published study, we generated and validated a new simplified comorbidity score (SCS) more disease specific in NSCLC patients [6]. In the first part of this study, 735 patients were screened for the relationship between common comorbidities and outcome in order to generate the SCS score. In a second step of the study, another population of patients were investigated in order to validate this new SCS score and to compare the respective prognostic values of CCI and SCS [6]. This study demonstrated that the SCS is an independent prognostic factor and appears more informative than the CCI in predicting NSCLC patient outcome. The survival analysis, however, only informed on short-term survival inasmuch as the median follow-up was 25.9 months (range 3.3–67.4 months). The short follow-up period and the relatively small size of the validation cohort urged a confirmative study in order to circumvent both limitations.
Lung cancer symptoms and psychological distress are a major burden for lung cancer patients and greatly contribute to QoL impairment. Several instruments have been developed and validated to assess QoL in the lung cancer patients population [8], yet their use is mainly limited to the clinical research setting. PS remains the key factor in therapeutic decision making and QoL is often considered as a less-potent clinical parameter and less easy to measure. Nevertheless, an exhaustive evaluation of factors contributing to NSCLC prognosis will need the simultaneous appraisal of PS, comorbidities and QoL.
This study aimed (i) at validating the SCS in a prospective bicentric NSCLC population treated according to the American Society of Clinical Oncology guidelines and (ii) at measuring the respective prognostic value of QoL, evaluated using the Lung Cancer Symptoms Scale (LCSS) [9] and comorbidity in regard to well-documented variables such as PS and stage.
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patients and methods |
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patients
In order to organise lung cancer care, we built since 1998 a health network of cancer institutions following common guidelines and willing to implement a prospective patient database (OncoLR) with institutional and national (Commission Nationale Informatique et Liberté) agreements. All patients newly diagnosed with histologically proven and previously untreated NSCLC entered the database. Consequently, patients admitted for adjuvant treatment (following surgery), second-line therapy or palliative care following anticancer treatment failure were not eligible. Histological subclassification was carried out according to the World Health Organisation classification [10]. ECOG PS was estimated before any therapy [11] and the percentage of weight loss during the previous 4 months was recorded. Staging was carried out by exhaustive procedures according to the sixth edition of the Union Internationale Contre le Cancer (UICC) tumour node metastases (TNM) classification [12].
pretherapeutic investigations
Work-up for each patient consisted of clinical examination, blood counts, blood chemistry [serum fibrinogen, sodium, calcium, proteins, albumin, alkaline phosphatases, lactate dehydrogenase (LDH), CYFRA 21-1 and neuron-specific enolase (NSE) levels], standard chest roentgenography, computed tomographic (CT) scan of chest, upper abdomen and brain, fiberoptic bronchoscopy and bone scanning. Fluorine-18 deoxyglucose (FDG) positron emission tomography (PET) scan was carried out according the current guidelines [13]. Patients suffering from locally advanced disease including mediastinal lymph node enlargement on chest CT scan or high FDG uptake on PET scan, but without the evidence of distant metastasis, underwent mediastinoscopy or videosurgery in order to establish nodal status.
comorbid index and QoL assessments
CCI and SCS comorbidity scales were evaluated before any treatment. Comorbid conditions included in the SCS are as follows: tobacco consumption, diabetes mellitus and renal insufficiency (respective weightings 7, 5 and 4), respiratory, neoplastic and cardiovascular comorbidities and alcoholism (weighting = 1 for each item) [6]. Finally, QoL evaluation was carried out at study admission using a validated French version of the LCSS patient scale [9]. The LCSS patient scale consists of nine items: six subscales related to major lung cancer symptoms (appetite, cough, dyspnoea, fatigue, haemoptysis, and pain), all using 100 mm visual analogue measurements, and three summation items (activity status, symptomatic distress and overall QoL).
therapy
A medical panel composed of thoracic surgeons, chest physicians, radiologists, radiotherapists and medical oncologists discussed the case of each patient in order to design a treatment programme to be submitted for patient's approval. Particular attention was paid to the agreement between each individual proposal and the medical guidelines.
NSCLC patients with stage I or II disease underwent surgery in an attempt at complete resection. Patients suffering from pathologically demonstrated N2 disease received cisplatin-based neoadjuvant chemotherapy followed by surgery whenever possible. Other patients with a performance status of 2 or less and distant metastases (stage IV) or gross mediastinal involvement (stage IIIb and unresectable stage IIIa) were treated when clinically possible by a cisplatin-based chemotherapy. Radiotherapy was applied in locally advanced stages according to a concurrent chemoradiotherapy schedule [14]. Best supportive care, including palliative radiation therapy when needed, was proposed to patients with advanced stage and poor PS. Treatment was decided upon according to clinical and routine biological findings and without knowledge of the SCS although some of the comorbid conditions were obviously taken into account in therapeutic choice (e.g. poor respiratory function and surgical contraindication). Hence, treatment was not considered as a prognostic variable in this study.
statistics
Survival was defined as the time from histological diagnosis to the date of death whatever the cause. Survival data were updated on 10 July 2006.
Coding methods for the different variables depended on their nature. Some of the variables were extensively described in the literature, therefore the threshold was defined using previous publications. PS was analysed according to two classical modalities: a performance status of zero to one and a performance status of two or more [11]. The same coding regarding tumour status has been adopted according to the new Mountain's stage grouping (stages I–IIIa versus stages IIIb–IV) [2]. Owing to the fact that the French guidelines are based on stage grouping according to the Mountain's system rather than the detailed TNM, we considered Mountain's stage grouping as the staging variable in the Cox model. TNM was not introduced in order to avoid statistical redundancy. For the biological variables, previously published thresholds were used particularly for CYFRA 21-1 and NSE serum levels [15].
Probability of survival was estimated by the Kaplan–Meier method [16]. Single variable survival analyses were assessed by means of the Wilcoxon and log-rank tests and multivariate regression was assessed with Cox model [17–19]. The classical forward selection of variable procedure was used. A P level <0.05 was considered significant. All tests were two-sided. Survival was analysed using the SAS software package. The complete procedures used in the Cox model are described in appendix.
The distribution of qualitative variables between groups was compared using the chi-square test or the Fisher's exact test (e.g. distribution of QoL items or global symptoms score according to clinicopathological prognostic determinants).
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results |
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A total of 301 consecutive NSCLC patients were prospectively accrued in our two university departments from September 2003 to April 2006. Patient's demography and disease characteristics are summarised in Table 1. At end point, two patients were lost to follow-up (0.7%). Median follow-up was 20.8 months (range 2.5–34.1 months) and 158 events were recorded. The median survival of the whole population was 17 months [95% confidence interval (CI) 13.5–22]. The 1- and 2-year survival rates were 59% (95% CI 54% to 65%) and 29% (95% CI 26% to 33%), respectively.
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quality of life
QOL features are displayed in Table 2. Marked low (unfavourable) scores were identified for three items (activity status, symptomatic distress and overall QoL). NSCLC patients complained from fatigue, dyspnoea and cough as the three most common symptoms. The median value of the global symptoms score was 22.2 and was used as cut-off for subsequent analyses. Global symptoms score was significantly (chi-square test; P < 0.05) higher in patients presenting with one of the following features: poor PS, advanced stage grouping, weight loss, high leukocyte count, high fibrinogen, CYFRA 21-1, LDH levels and low serum albumin level. In addition, there was a trend towards a significant relationship between a high global symptoms score and high CCI (P = 0.0508). Fatigue score was significantly associated with PS, weight loss, leukocyte count, fibrinogen and LDH levels. Cough score was significantly associated with stage grouping, weight loss, CCI, SCS, fibrinogen and albumin levels. Dyspnoea score was significantly associated with fibrinogen level. Haemoptysis score was significantly associated with PS, weight loss and serum calcium level. Pain score was significantly associated with PS, stage grouping, weight loss, leukocyte and platelet count, fibrinogen, CYFRA 21-1, NSE and alkaline phosphatases levels. Activity status item was significantly associated with PS, stage grouping, weight loss, platelet count, fibrinogen, alkaline phosphatases, LDH and albumin levels. Symptomatic distress item was significantly associated with PS, stage grouping, weight loss, fibrinogen, CYFRA 21-1, LDH, alkaline phosphatases, protein and albumin levels. Finally, a poor overall QoL item was significantly associated with the following features: poor PS, advanced stage grouping, weight loss, high leukocyte count, high fibrinogen level, hypercalcaemia, high LDH level and low albumin level. There was no statistically significant association between any of the QoL items and age, NSCLC histological subclassification, haemoglobin level, lymphocytes count and serum sodium level.
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univariate analysis
The univariate analysis (Table 3) showed that patients affected by one of the following characteristics proved to have a shorter survival in comparison with the opposite status of each variable: poor PS, advanced stage, weight loss, anaemia, hyperleukocytosis, lymphopenia, high platelet count, high CYFRA 21-1, high NSE, hypoprotidemia, hypoalbuminemia, high LDH, high alkaline phosphatases, hyponatremia, hypercalcaemia, high fibrinogen, SCS >9, CCI
3 and patient LCSS score >22.2. In addition, there was a trend towards a significant negative prognostic effect for a nonadenocarcinomatous histology. Survival according to CCI, SCS and patient LCSS values are shown in Figures 1–3, respectively.
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multivariate analysis
The following variables were independent determinants of a poor outcome: stage grouping, hazard ratio (95% CI): 4.03 (2.40–6.77); CYFRA 21-1 level: 2.30 (1.52–3.49); low QoL: 2.20 (1.48–3.27); SCS: 1.78 (1.21–2.63); anaemia: 1.88 (1.16–3.07); high NSE level: 1.66 (1.12–2.46); low sodium level: 1.99 (1.04–3.77) and high alkaline phosphatases level: 1.53 (1.01–2.32).
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discussion |
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The impact of comorbid conditions on prognosis might be of paramount importance in such an heavy-smoking population as are NSCLC patients. A recent study demonstrated that an unfavourable CCI score was associated with a poor prognosis in two large phase III NCIC trials [20]. Interestingly, the analysed population yielded a low incidence of comorbid conditions inasmuch as 69% of patients had a CCI score = 0. This study exemplified that, patients afflicted by common comorbidities are frequently excluded from clinical trials. However, when considering the CCI in a general (unselected) population of lung cancer, one can easily observe that 25% of the patients are afflicted by a CCI
3 [6]. Therefore, the study reported here attempting at determining QoL and comorbidity impacts in survival of NSCLC patients in daily practice could be regarded as complementary. Population characteristics of our presentstudy and the results of univariate analyses are in accordance with current worldwide patient's demography and disease characteristics of NSCLC. The overall prognosis of the whole population is consistent with what is observed in an unselected NSCLC. In the multivariate analysis, several characteristics were identified as independent determinants of a shorter survival: stage grouping, CYFRA 21-1 level, anaemia, high NSE level, hyponatremia, high alkaline phosphatases level, unfavourable SCS and low patient LCSS QoL at time of diagnosis. The first six variables are well-identified NSCLC prognostic factors [2, 15, 21–24]. The remaining two variables, respectively, evaluating comorbidity and pretherapeutic QoL deserve specific comments.
Hitherto, the impact of comorbid conditions might have been underestimated even if a literature on this topic have had recently arose [4, 6, 25, 26]. In our previous study, we developed for in a large, unselected NSCLC population, and validated into an independent population a new SCS. This score considers tobacco consumption together with clinical comorbid conditions (diabetes mellitus, renal insufficiency, respiratory, neoplastic and cardiovascular comorbidities) and alcoholism. A SCS >9 was found to be an independent prognostic factor of poor outcome and appeared more informative than the CCI in predicting patient outcome in the setting of NSCLC patients. The herein larger appraisal of SCS prognostic significance in an extended study confirms thesis observations.
QoL is a clinical parameter increasingly used in the assessment of health status and the impact of therapeutic applications in numerous diseases, including lung cancer patients. The assessment of QOL involves comprehensive measurement tools that address the physical, social, functional and emotional well-being of the patient. Such measurements should be easy to use, meaningful and relevant to the patients and clinician. It has been suggested that a broad QoL evaluation using current well-structured instruments can provide additional prognostic information in a lung cancer population, using the Functional Living Index-Cancer [27], the European Organisation for Research and Treatment of Cancer questionnaires [28], the Functional Assessment of Cancer Therapy—Lung questionnaire [29] or the LCSS assessment [30]. Routine QoL assessment, however, is seldomly considered in the pretherapeutic work-up, due to its time-consuming assessment and the uncertainty of its immediate clinical implication.
In this study, pretreatment CCI did not enter the Cox model probably because SCS and CCI shared redundant prognostic information and SCS was retained as independent prognostic factor. In addition, pretreatment patient-assessed QoL was identified as an independent prognostic factor. This finding reinforces the thesis that QoL is not only an end point to be considered in controlled studies but might have also been analysed as an important prognostic indicator. It is, however, noteworthy that the adjunction of SCS and LCSS score, as new prognostic determinants, is resulting in the removal of ECOG PS from the Cox model. The combination of comorbidities evaluation using the SCS and self-evaluation of LCSS scale appeared more informative than PS in defining outcome of that population. A possible explanation for this phenomenon could be a redundancy of the prognostic information shared in common by PS and QoL [30]. One can consider the later variable as more accurately reflecting patient global health status owing to the fact that LCSS is assessed by the patient himself, whereas PS assessment by physicians could be less objective.
In conclusion, the inclusion of both comorbidity and QoL evaluations in NSCLC patients work-up might enhance the prognostic information and could be taken into account when designing clinical trials in this disease.
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funding |
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Supported by grants from OncoLR Heath Network.
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appendix |
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The variables to be tested in the Cox model were selected using the results of univariate analyses i.e. variables reaching at least a P <0.15. This model was written after a Boolean coding of the significant variables: categorical variables (such as performance status) were transformed into binary variables (0: negative or 1: positive). The number of levels of a Boolean variable needed to describe a predictive factor is one less than the categories of that factor inasmuch as its baseline level is defined by setting the value of each of the Boolean variables at zero. The significance of the effect of a given factor was assessed by determining whether or not the coefficient assigned to one or more of its categories was sufficiently different to zero. The proportional hazard assumption for each of the selected variables retained in the final model was initially checked by plotting the log cumulative baseline hazard ratio.
The above-mentioned procedure identified 20 variables as putative prognostic determinants to be tested in the Cox regression hazards model. The proportional hazard assumption, however, was rejected concerning fibrinogen, protein and albumin serum levels. Therefore, 17 variables were tested in the Cox regression hazards model. This almost complied with the classical recommendation by Harrell [19] suggesting that the number of variables tested must represent <10% of the total of observed events.
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Footnotes |
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Present address: Respiratory Diseases Unit, Hôpital Saint Joseph, 6, rue de la Duchère, B-6060 Gilly, Belgium. 
Received for publication January 23, 2008. Accepted for publication February 14, 2008.
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References |
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