Pretreatment Quality of Life and Functional Status Assessment Significantly Predict Survival of Elderly Patients With Advanced Non—Small-Cel
http://www.100md.com
《临床肿瘤学》
the S Giuseppe Moscati Hospital, Avellino
National Cancer Institute
Medical Statistics, Second University of Napoli
Pneumology V, Monaldi Hospital, Napoli
S Carlo Hospital, Potenza
Mariano Santo Hospital, Cosenza
S Giovanni di Dio e Ruggi d'Aragona, Salerno
Civil Hospital, Noale, Venezia
Sacco Hospital
S Gerardo Hospital, Monza, Milano
Civil Hospital, Rovereto, Trento
Molinette Hospital
San Luigi Gonzaga Hospital, Orbassano, Torino
Forlanini Hospital
Instituto Nazionale Ripose e Cura Anziani, Roma
Civil Hospital, Padova
Pneumology, University of Palermo, Palermo
S Vincenzo Hospital, Taormina, Catania
Centro di Riferimento Oncologico, Aviano, Pordenone, Italy
ABSTRACT
PURPOSE: To study the prognostic value for overall survival of baseline assessment of functional status, comorbidity, and quality of life (QoL) in elderly patients with advanced non—small-cell lung cancer treated with chemotherapy.
PATIENTS AND METHODS: Data from 566 patients enrolled onto the phase III randomized Multicenter Italian Lung Cancer in the Elderly Study (MILES) study were analyzed. Functional status was measured as activities of daily living (ADL) and instrumental ADL (IADL). The presence of comorbidity was assessed with a checklist of 33 items; items 29 and 30 of the European Organisation for Research and Treatment of Cancer (EORTC) core questionnaire QLQ-C30 (EORTC QLQ-C30) were used to estimate QoL. ADL was dichotomized as none versus one or more dependency. For IADL and QoL, three categories were defined using first and third quartiles as cut points. Comorbidity was summarized using the Charlson scale. Analysis was performed by Cox model, and stratified by treatment arm.
RESULTS: Better values of baseline QoL (P = .0003) and IADL (P = .04) were significantly associated with better prognosis, whereas ADL (P = .44) and Charlson score (P = .66) had no prognostic value. Performance status 2 (P = .006) and a higher number of metastatic sites (P = .02) also predicted shorter overall survival.
CONCLUSIONS: Pretreatment global QoL and IADL scores, but not ADL and comorbidity, have significant prognostic value for survival of elderly patients with advanced non—small-cell lung cancer who were treated with chemotherapy. Using these scores in clinical practice might improve prognostic prediction for treatment planning.
INTRODUCTION
Non—small-cell lung cancer (NSCLC) is a group of heterogeneous clinical entities with different clinical behaviors and prognoses. As is true for many other types of tumors, the proportion of NSCLC patients aged 70 years or older is constantly increasing in industrialized countries because of the gain in life expectancy observed in the second part of the last century, and this trend is expected to continue in the next decades.1
In addition to classical prognostic factors for advanced NSCLC including performance status (PS) and the extent of disease,2 elderly cancer patients have peculiar characteristics that may affect prognosis. In this regard, a pretreatment geriatric assessment, including evaluation of comorbidity, functional status, depression, cognitive impairment, nutritional status, and social support, has been proposed to assess prognosis and predict toxicity.3-5 However, the advantage of such a comprehensive assessment is probably outweighed by the disadvantage of its poor applicability in clinical practice.
The assessment of comorbidity and the evaluation of functional status are among the most important constituents of a comprehensive geriatric assessment. Comorbidity may be summarized according to several scales.6,7 Functional status refers to the ability of the patient to perform daily functions. Assessment of PS is the most widely used functional score in oncology, however, it has been suggested that this score might underestimate the degree of functional impairment, particularly in the elderly subset of patients.3 The most widely used functional impairment geriatric scales are Katz's basic Activities of Daily Living (ADL)8 and Lawton's9 Instrumental Activities of Daily Living (IADL). Although these geriatric scales may produce additional information on the functional assessment of elderly cancer patients, their prognostic role in elderly patients with advanced NSCLC is unknown.
The Multicenter Italian Lung Cancer in the Elderly Study—01 (MILES-01)10 was a large prospective randomized trial of chemotherapy dedicated to elderly patients with advanced NSCLC. This study showed that polychemotherapy with gemcitabine plus vinorelbine was not more effective than gemcitabine alone and vinorelbine alone. A previous study by the same group of investigators,11 the phase III Elderly Lung Cancer Vinorelbine Italian Study (ELVIS) study, showed that vinorelbine was better than supportive care in elderly patients with advanced NSCLC. Also in that study, we found that the baseline scores of items 29 and 30 of the European Organisation for Research and Treatment of Cancer (EORTC) core questionnaire QLQ-C30 predicted time to dropout from the study; patients with worse scores tended to drop out earlier than patients with higher scores.11
The current study was planned a priori in the MILES protocol to explore the possible prognostic role of ADL, IADL, and comorbidity. Following the reported results of the ELVIS study, we also included quality of life measured with items 29 and 30 of EORTC QLQ-C30 as a covariate of prognostic analysis.
PATIENTS AND METHODS
Patients and Treatment
Patients with advanced NSCLC enrolled onto the MILES study10 were 70 years old or older, had stage IV or IIIB disease with supraclavicular metastatic nodes or malignant pleural effusion, and a baseline PS not worse than 2, according to the Eastern Cooperative Oncology Group (ECOG) scale. The MILES study compared the combination of vinorelbine and gemcitabine with the two drugs given singly. Patients were randomly assigned to receive vinorelbine (30 mg/m2), gemcitabine (1,200 mg/m2), or gemcitabine (1,000 mg/m2) plus vinorelbine (25 mg/m2). All treatments were administered on days 1 and 8 every 3 weeks for six cycles of 21 days. The primary end point of the study was overall survival. Of 707 patients randomly assigned between December 1997 and November 2000, 566 patients (80%) with complete information on baseline ADL, IADL, and quality of life were included in this prognostic analysis.
Global Health Status/Quality of Life
To assess quality of life, the EORTC QLQ-C3012 and the EORTC lung cancer—specific module QLQ-LC1313 were used. In the current analysis, only one score was used, the global health status/quality of life (QoL), calculated with responses to items 29 and 30 of EORTC QLQ-C30. In response to these two items, patients were asked to grade their global health status (item 29) and quality of life (item 30) during the previous week on a scale of 7 points. A raw score was calculated for each patient and linearly transformed in a percent scale ranging from 0 to 100, 0 representing the lowest level of global quality of life and 100 the highest. In this analysis, patients were grouped in three score categories using first and third quartiles as cut points: "better" (scoring > 67%, roughly representing the highest quarter of the distribution), "intermediate" (scoring 43% to 67%, about half of subjects), and "worse" (scoring 42%, representing the lowest quarter of the distribution).
Geriatric Assessment
Concomitant pathologies were scored as absent/present using a predefined list of 33 possible diseases. Comorbidity was summarized by the Charlson score,6 summing up data regarding myocardial infarction, congestive heart failure, peripheral vascular disease, cerebral vascular disease, dementia, chronic obstructive pulmonary disease, connective tissue disease, ulcer disease, mild liver disease and diabetes. The other pathologic conditions (hemiplegia, moderate or severe renal disease, diabetes with organ damage, any other cancer, moderate or severe liver disease, AIDS) used to calculate the Charlson score were not taken into account because they were precluded by exclusion criteria for the study. Consequently, higher scores were rarely attained, and just four categories were used in the analysis (0, 1, 2, 3).
Functional status of elderly patients was measured by ADL and IADL scores that were recorded at baseline, before randomization, by physicians.
ADL8 includes bathing, dressing, using the bathroom, continence, getting up and being able to move around the house, and feeding. For each of the six items, two possible scores were assigned: 0 (dependent) or 1 (independent). Thus, the ADL score for each patient ranged from 0 (unable to perform any activity) to 6 (able to perform all activities). Because of the high prevalence of patients scoring 6, two groups were arbitrarily created for this analysis: fully independent (score 6) and 1 dependency (scores < 6).
IADL9 includes the ability to use the telephone, shopping, food preparation, housekeeping, handyman work, laundry, the ability to get around outside the home, responsibility for own medications, and the ability to handle finances. For each item four responses are available, three representing varying degrees of dependency (all assigned score 0) and one representing full independency (score 1). Some of the explored domains (eg, cooking, washing clothes, and so on) are fully applicable only to women, considering the advanced age of the population. Thus, missing data within the forms were frequent among men. To accommodate this phenomenon, a raw score was calculated considering only questions that had been answered by the patients, on the assumption that missing values were primarily due to inapplicability of the question. Such score was linearly transformed in a percent scale ranging from 0 to 100, 0 representing the lowest level of ability and 100 the highest. For prognostic and correlation analyses, patients were arbitrarily grouped in three score categories: "better" (scoring 100%, roughly representing the best quarter), "intermediate" (scoring 51% to 99%, about half of the subjects), and "worse" (scoring 0% to 50%, representing the worst quarter).
Statistical Methods
Associations between baseline ADL, IADL, and QoL categories and characteristics of patients were studied by contingency tables and the 2 test.
Overall survival was defined as the time elapsed from the date of randomization to the date of death or the date of the last follow-up for patients alive at the end of the study. Multivariate survival analysis was done using the Cox model,14 and was stratified by treatment arm. Because of the high number of events, a simple strategy was undertaken by a single model including all known or potential prognostic factors (age, sex, stage, histotype, number of sites of disease, baseline QoL, ADL, IADL, and Charlson score) and a variable representing institutions by number of patients enrolled (< 10, 10-29, 30) as a possibly confounding covariate. The likelihood ratio test was used to test the contribution of each variable to the model when added last, that is after adjustment for all of the other covariates. P values less than .05 were considered statistically significant. Overall survival curves were drawn by the Kaplan-Meier method.15
RESULTS
Patient Characteristics
Median age of the patients was 74 years (range, 70 to 84 years); 229 patients (40%) were 75 years old or older (Table 1). Men represented 82% of the population. Institutions that enrolled more than 30 patients comprised about one fourth of the patients; those that enrolled between 10 and 29 patients comprised about half the patients.
More patients with stage IV disease than stage III disease were enrolled, representing 69% of the sample (Table 2). Squamous cell carcinoma was the most prevalent histologic type (45% of patients), followed by adenocarcinoma (34%). Patients had a median of three organs affected by cancer. Nineteen percent of patients had a deteriorated baseline PS (ECOG category 2). Approximately 90% of the patients had at least one and approximately 40% had three or more comorbidities; only 11% of patients had no comorbidity. According to the Charlson score, 42% of patients were in the lowest category (score 0).
QoL, ADL, IADL, and Charlson score
Distribution of baseline QoL, ADL, and IADL in the population is illustrated in Figure 1. QoL was distributed symmetrically, with the majority of patients reporting intermediate scores. Conversely, both ADL and IADL distributions were highly skewed, the best score being most frequent (85% and 33% for ADL and IADL, respectively).
PS was significantly correlated with QoL, ADL, and IADL scores. All the scores were worse among patients with PS2 (Table 2; all P values < .0001), whereas Charlson score was only associated with IADL, being lower in patients with higher IADL scores (P = .005).
Overall Survival
Of 566 patients eligible for prognostic analysis, 462 patients (82%) died. Median overall survival for patients was 30 weeks (95% CI, 28 to 34), and 6-month and 1-year probabilities of overall survival were 0.56 and 0.32, respectively.
Results of multivariate analysis are reported in Table 3. After adjusting for the other covariates, QoL and IADL were associated with prognosis (P = .0003 and P = .04, respectively), whereas ADL was not (P = .44). A low PS (ECOG score 2) and the number of metastatic sites also independently predicted worse overall survival rates (P =.006 and P = .02, respectively). Charlson score was not associated with prognosis; the results were superimposible if the total number of comorbidities was used instead of the Charlson score. Kaplan-Meier—estimated overall survival curves for QoL and IADL are shown in Figure 2.
DISCUSSION
A significant amount of both clinical and basic research has focused on the prognostic factors for patients with NSCLC. Although the prognosis of patients with advanced NSCLC is ominous overall, the identification of prognostic factors can be useful, not only for providing important information to the patients, but also for the correct choice of treatment. The latter issue is particularly relevant for elderly patients, because of the concerns about generalizability of treatment effects demonstrated in younger patients16 and poor tolerability of treatments.
Within a secondary analysis of the MILES study, we looked for new tools to predict the prognosis of elderly patients at the time of diagnosis and before chemotherapy treatment. Specifically, we studied the prognostic value of the patient's self-assessment of QoL and physician's assessment of functional scales (ADL and IADL) and comorbidity.
As for comorbidity, we recognize that a limitation of the present study consists of the use of a qualitative yes/no checklist, which does not result in information about the severity of concomitant diseases. This choice was pragmatically based on the principle of reducing the time needed to assess patients at baseline. A similar scale has been used previously by Repetto et al.5 The Charlson score,6 which was used as a summary measure of comorbidity, revealed no prognostic value in the MILES study. Although the potential prognostic role of the Charlson score was limited by the fact that eligibility criteria of the study excluded patients with higher scores, this finding is consistent with those recently reported by Janssen-Heijnen et al 17 showing that among 4,072 patients diagnosed with NSCLC in the Netherlands between 1995 and 1999, the number of comorbidities (collected according to a slightly modified version of the Charlson score) had no prognostic value for overall survival. A possible explanation of the lack of prognostic relevance of comorbidity in advanced lung cancer is reported in a recent paper by Read et al.18 The authors found that among 11,558 cancer patients, concurrent comorbidities had no relevant prognostic impact for groups of patients with the lowest overall survival rates, including 1,005 patients with advanced lung cancer. Whether different and more detailed definitions of comorbidity can produce useful prognostic information in the setting of advanced NSCLC remains to be seen.19,20 However, a study by Piccirillo et al21 of elderly patients with head and neck cancer suggests that general comorbidity indexes (like the Charlson score) perform similarly to disease-specific comorbidity indexes, and both types of scores are only able to weakly predict prognosis.
In contrast with the established prognostic value of ADL in nononcologic geriatric patients,22 baseline ADL had no prognostic value in the MILES population. A possible explanation could be that the prognostic value of ADL, as that of comorbidity,18 may only be truly effective in populations with a life expectancy longer than that of patients with advanced NSCLC. In addition, we should consider that dependencies in ADL represent quite severe deficiencies that probably prevent patients from being considered eligible for chemotherapy and for clinical trials. On the contrary, we found that baseline IADL had an independent prognostic role, that appears mostly relevant for the lower quarter, ie, the worse category. IADL is a quite easy-to-use instrument, but its application is limited by the fact that some domains (eg, cooking, washing clothes, and so on) are not effectively applicable to male patients, particularly if they are elderly. To accommodate this phenomenon, we ignored missing data and calculated a raw score based on available answers; this might reduce reproducibility of the present result.
Another important observation of our study was that baseline self-assessment of QoL, with two simple questions, was the strongest prognostic factor among elderly patients with advanced NSCLC enrolled onto the MILES trial; the major difference being evident between the upper quarter (ie, the better category) and the other categories that appear to have similar prognosis. To our knowledge, the present study reports the largest analysis on the prognostic role of QoL score in advanced NSCLC and the first analysis on the important subset of elderly patients. Indeed, Ganz et al23 reported on the importance of the Functional Living Index—Cancer24 in 40 patients. Montazeri et al25 reported that in a series of 129 patients global QoL measured by the EORTC C-30 questionnaire was significantly lower among the 30 patients who died within 3 months, as compared with the rest of the patients in the study. Langendijk et al26 reported similar results with the EORTC C-30 questionnaire with patients with lung cancer undergoing potentially curative radiation therapy. These results are in slight contrast with the observations of Herndon et al27 on 206 patients enrolled onto the Cancer and Leukemia Group B 8931 trial; they found that although several items of the EORTC C-30 questionnaire (including the overall QoL score) were correlated with prognosis at univariate analysis, only the pain score was retained in the final multivariate model.
In addition to providing crucial prognostic information, QoL assessment may be useful to improve communication with the patient and help the clinician to design tailored supportive treatments based on the correct identification of the overall burden of symptoms, the relative importance given to each of them by the patient, and his or her expectations regarding treatment's efficacy. As an example of poor patient-physician communication, even in the setting of randomized clinical trials, we have recently reported28 that pain measured by the pain scores included in the EORTC C-30 and LC-13 questionnaires is frequently undertreated by physicians, particularly when instrumental staging is negative for bone metastases. Thus, we suggest that the use of QoL instruments in clinical practice could help physicians improve their control of the patient's symptoms. Indeed, the feasibility and utility of a comprehensive assessment of elderly cancer patients, also when based on self-report methodology like QoL questionnaires, has been proven.29
In conclusion, quality of life and functional status assessment, by items 29 and 30 of the EORTC C-30 questionnare and the IADL scale, respectively, could be used in clinical practice as prognostic factors to aid the selection of elderly patients with advanced NSCLC for chemotherapy.
Appendix
List of institutions and coauthors. National Cancer Institute, Napoli: *Medical Oncology B (Cesare Gridelli, Emiddio Barletta, Maria Luisa Barzelloni, Rosario Vincenzo Iaffaioli) and Clinical Trials Unit (Francesco Perrone, Paolo Maione, Ermelinda De Maio, Massimo Di Maio, Gianfranco De Feo). Medical Statistics, Second University of Napoli (Ciro Gallo, Giuseppe Signoriello, Paolo Chiodini). *III Internal Medicine, University Federico II of Napoli (Silvio Cigolari,** Angela Cioffi, Vincenzo Guardasole, Valentina Angelini). *S Carlo Hospital, Potenza (Luigi Manzione, Antonio Rossi, Domenico Bilancia, Domenico Germano). Pneumology V, Monaldi Hospital, Napoli (Francovito Piantedosi, Alfredo Lamberti, Vittorio Pontillo, Luigi Brancaccio). Mariano Santo Hospital, Cosenza (Santi Barbera, Francesco Renda, Francesco Romano). Sacco Hospital, Milan (Elena Piazza, Gabriella Esani, Anna Gambaro). Medical Oncology, Noale—VE (Orazio Vinante, Francesco Rosetti, Giuseppe Azzarello). S Giuseppe Hospital, Milano (Maurizia Clerici, Roberto Bollina, Paolo Belloni). S Maria del Carmine Hospital, Rovereto—TN (Sergio Federico Robbiati, Mirella Sannicolò). Molinette Hospital, Torino (Oscar Bertetto, Libero Ciuffreda, Giuseppe Parello). S Paolo Hospital, Milano (Luciano Frontini, Mary Cabiddu#). S Maria della Misericordia Hospital, Udine (Cosimo Sacco, Angela Sibau). San Lazzaro Hospital, Alba—CN (Gianfranco Porcile, Federico Castiglione, Oliviero Ostellino). Civil Hospital, Padova (Silvio Monfardini, Adolfo Favaretto, Micaela Stefani). San Luigi Gonzaga Hospital, Orbassano—TO (Giorgio Scagliotti, Silvia Novello, Giovanni Selvaggi). Forlanini Hospital, Roma (Filippo De Marinis, Maria Rita Migliorino, Olga Martelli). Medical Oncology, Az Ospedaliera "Bianchi-Melacrino-Morelli", Reggio Calabria (Giampietro Gasparini,? Alessandro Morabito,? Domenico Gattuso). *Experimental Medical Oncology, Oncologic Institute, Bari (Giuseppe Colucci, Domenico Galetta, Francesco Giotta). *Medical Oncology, University of Palermo (Vittorio Gebbia). *La Maddalena Hospital, Palermo (Nicola Borsellino, Antonio Testa). *S Vincenzo Hospital, Taormina—CT (Francesco Ferraù, Emilia Malaponte). Thoracic Surgery, University of Foggia (Matteo A. Capuano, Michele Angiolillo, Francesco Sollitto). Medical Oncology, CRO, Aviano—PN (Umberto Tirelli, Alessandra Bearz, Simona Spazzapan). Medical Oncology, University of Messina (Vincenzo Adamo, Giuseppe Altavilla, Antonino Scimone). Pneumology, University of Palermo (Mario Spatafora, Maria Raffaella Hopps, Francesco Tartamella). G. Rummo Hospital, Benevento (Giovanni Pietro Ianniello, Vincenza Tinessa). S Luigi and S.S. Currò Gonzaga Hospital, Catania (Giuseppe Failla, Roberto Bordonaro). Chemotherapy, University of Palermo (Nicola Gebbia, Maria Rosaria Valerio). *S Maria Goretti Hospital, Latina (Modesto D'Aprile, Enzo Veltri), Latina. Medical Oncology, University of Perugia (Maurizio Tonato, Samir Darwish). *Cardarelli Hospital, Campobasso (Sante Romito, Francesco Carrozza). S Gerardo Hospital, Monza—MI (Sandro Barni,# Antonio Ardizzoia). USSL 33, Rho—MI (Giuliana Mara Corradini, Gianfranco Pavia). *Civil Hospital, Avellino (Mario Belli, Giuseppe Colantuoni). S Chiara Hospital, Trento (Enzo Galligioni, Orazio Caffo). Medical Oncology, Spedali Riuniti, Bergamo (Roberto Labianca, Antonello Quadri). Medical Oncology, University La Sapienza, Roma (Enrico Cortesi, Giuliana D'Auria). Civil Hospital, Legnano— MI (Sergio Fava, Anna Calcagno). S Carlo Borromeo Hospital, Milano (Gino Luporini, M. Cristina Locatelli). S Maria Hospital, Terni (Francesco Di Costanzo, Silvia Gasperoni). Serbelloni Hospital, Gorgonzola—MI (Luciano Isa, Paola Candido). USSL 15, Camposampiero—PD (Fernando Gaion, Giovanni Palazzolo). *Miulli Hospital, Acquaviva delle Fonti—BA (Giuseppe Nettis, Anselmo Annamaria). *Medical Oncology II, "Regina Elena" Institute, Roma (Massimo Rinaldi, Massimo Lopez). S Martino Hospital, Genova (Raffaella Felletti, Giorgio Bernabò Di Negro). *Civil Hospital, Polla—SA (Nestore Rossi, Antonio Calandriello). San Gennaro Hospital, Napoli (Luigi Maiorino). S Croce Hospital, Fano—PS (Rodolfo Mattioli). S Giovanni Hospital, Torino (Alfredo Celano). S Bortolo Hospital, Vicenza (Stefania Schiavon). Oncology, Monaldi Hospital, Napoli (Alfonso Illiano). Cottolengo Hospital, Torino (Carlo Alberto Raucci). *Oncologic Center, Catania (Michele Caruso). Medical Oncology, University of Milano (Paolo Foa||). Medical Oncology, Biomedical Campus, Roma (Giuseppe Tonini). Thoracic Surgery, Ascalesi Hospital, Napoli (Carlo Curcio). Civil Hospital, Treviglio—BG (Marina Cazzaniga). Pneumology, Spedali Riuniti, Bergamo. Medical Oncology I, IST, Genova. *Fatebenefratelli Hospital, Benevento. *Medical Oncology, University of Cagliari. Businco Hospital, Cagliari. Agnelli Hospital, Pinerolo— TO. SS Trinità Hospital, Sora—FR. S Andrea Hospital, Vercelli. Civil Hospital, Gorizia. Medical Oncology, University of Sassari. Civil Hospital, Bolzano. Fortunato Hospital, Rionero in Vulture—PZ. *Da Procida Hospital, Salerno. C Cantù Hospital, Abbiategrasso—MI. Pugliese Ciaccio Hospital, Catanzaro. Civil Hospital, Rovigo. S Maria delle Grazie Hospital, Pozzuoli—NA. Civil Hospital, S Felice a Cancello—CE. *Galateo Hospital, S.Cesareo—LE. Civil Hospital, Lagonegro—PZ. *Civil Hospital, Sciacca—AG.
NOTE: (*) denotes Institutions that participate in the activities of the Gruppo Oncologico Italia Meridionale; () S Giuseppe Moscati Hospital, Avellino; ()DaProcida Hospital, Salerno; () S Gerardo Hospital, Monza; (||) S Paolo Hospital, Milano; (?) S Filippo Neri Hospital, Roma; (#) Civil Hospital, Treviglio (BG); (**) S Giovanni di Dio e Ruggi d'Aragona, Salerno; () Monaldi Hospital, Napoli.
Authors' Disclosures of Potential Conflicts of Interest
Although all authors completed the disclosure declaration, the following authors or their immediate family members indicated a financial interest. No conflict exists for drugs or devices used in a study if they are not being evaluated as part of the investigation. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.
Acknowledgment
We thank Federika Crudele, Giuliana Canzanella, Fiorella Romano, and Assunta Caiazzo for data management and secretarial assistance; Alfonso Savio for hardware and software assistance; and the Gruppo Oncologico Italia Meridionale (GOIM) for promoting the study among its associated centers.
NOTES
Supported in part by Associazione Italiana per la Ricerca sul Cancro (AIRC), Clinical Trials Promoting Group (CTPG), and Gruppo Italiano di Oncologia Geriatrica (GIOGer). P.M. is the recipient of an AIRC fellowship.
Presented in part at the 38th Annual Meeting of the American Society of Clinical Oncology, Orlando, FL, May 18-21, 2002 (poster).
Authors' disclosures of potential conflicts of interest are found at the end of this article.
REFERENCES
Ries LAG, Eisner MP, Hankey BF, et al: SEER Cancer Statistic Review, 1973-1998. Bethesda, MD, National Cancer Institute, 2001
Brundage MD, Davies D, Mackillop WJ: Prognostic factors in non-small cell lung cancer: A decade of progress. Chest 122:1037-1057, 2002
Inouye SK, Peduzzi PN, Robison JT, et al: Importance of functional measures in predicting mortality among older hospitalized patients. JAMA 279:1187-1193, 1998
Balducci L: Geriatric oncology: Challenge for the new century. Eur J Cancer 36:1741-1754, 2000
Repetto L, Fratino L, Audisio A, et al: Comprehensive geriatric assessment adds information to Eastern Cooperative Oncology Group Performance status in elderly cancer patients: An Italian Group for Geriatric Oncology study. J Clin Oncol 20:494-502, 2002
Charlson ME, Pompei P, Ales K, et al: A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 40:373-383, 1987
Satariano WA, Ragland DR: The effect of comorbidity on 3-year survival of women with primary breast cancer. Ann Intern Med 120:104-110, 1994
Katz S: Assessing self maintenance: Activities of daily living, mobility and instrumental activities of daily living. J Am Geriatr Soc 31:721-727, 1983
Lawton MP, Brody EM: Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 9:179-186, 1969
Gridelli C, Perrone C, Gallo C, et al: Chemotherapy for elderly patients with advanced non-small cell lung cancer: The MILES (Multicenter Italian Lung Cancer in the Elderly Study) phase 3 randomized trial. J Natl Cancer Inst 95:362-372, 2003
Elderly Lung Cancer Vinorelbine Italian Study Group: Effects of vinorelbine on quality of life and survival of elderly patients with advanced non-small-cell lung cancer. J Natl Cancer Inst 91:66-72, 1999
Aaronson NK, Ahmedzai S, Bergman B, et al: The European Organization for Research and Treatment of Cancer QLQ-C30: A quality of life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 85:365-376, 1993
Bergman B, Aaronson NK, Ahmedzai S, et al: The EORTC QLQ-LC13: A modular supplement to the EORTC core quality of life questionnaire (QLQ-C30) for use in lung cancer clinical trials. Eur J Cancer 30A:635-642, 1994
Cox DR: Regression models and life tables. J R Stat Soc B 34:187-220, 1972
Kaplan EL, Meier P: Non parametric estimation from incomplete observation. J Am Stat Assoc 53:457-481, 1958
Perrone F, Gallo C, Gridelli C: Re: Cisplatin-based therapy for elderly patients with advanced non-small-cell lung cancer: Implications of Eastern Cooperative Oncology Group 5592—A randomized trial. J Natl Cancer Inst 94:1029-1030, 2002 (letter)
Janssen-Heijnen MLG, Smulders S, Lemmens VEPPP, et al: Effect of comorbidity on the treatment and prognosis of elderly patients with non-small cell lung cancer. Thorax 59:602-607, 2004
Read WL, Tierney RM, Page NC, et al: Differential prognostic impact of comorbidity. J Clin Oncol 22:3099-3103, 2004
Piccirillo JF, Tierney RM, Costas I, et al: Prognostic importance of comorbidity in a hospital-based cancer registry. JAMA 291:2441-2447, 2004
Repetto L, Venturino A, Fratino L, et al: Geriatric oncology: A clinical approach to the older patient with cancer. Eur J Cancer 39:870-880, 2003
Piccirillo JF, Spitznagel EL, Vermani N, et al: Comparison of comorbidity indices for patients with head and neck cancer. Med Care 42:482-486, 2004
McCusker J, Bellavance F, Cardin S, et al: Detection of older people at increased risk of adverse health outcomes after an emergency visit: The ISAR screening tool. J Am Geriatr Soc 47:1229-1237, 1999
Ganz PA, Lee JJ, Siau J: Quality of life assessment: An independent prognostic variable for survival in lung cancer. Cancer 67:3131-3135, 1991
Schipper H, Clinch J, McMurray A, et al: Measuring the quality of life of cancer patients: The Functional Living Index-Cancer—Development and validation. J Clin Oncol 2:472-483, 1984
Montazeri A, Milroy R, Hole D, et al: Quality of life in lung cancer patients as an important prognostic factor. Lung Cancer 31:233-240, 2001
Langendijk H, Aaronson NK, de Jong JM, et al: The prognostic impact of quality of life assessed with the EORTC QLQ-C30 in inoperable non-small cell lung carcinoma treated with radiotherapy. Radiother Oncol 55:19-25, 2000
Herndon JE, Fleishman S, Kornblith AB, et al: Is quality of life predictive of the survival of patients with advanced non-small cell lung carcinoma? Cancer 85:333-340, 1999
Di Maio M, Gridelli C, Gallo C, et al: Prevalence and management of pain in Italian patients with advanced non-small-cell lung cancer. Br J Cancer 90:2288-2296, 2004
Ingram SS, Seo PH, Martell RE, et al: Comprehensive assessment of the elderly cancer patient: The feasibility of self-report methodology. J Clin Oncol 20:770-775, 2002(Paolo Maione, Francesco P)
National Cancer Institute
Medical Statistics, Second University of Napoli
Pneumology V, Monaldi Hospital, Napoli
S Carlo Hospital, Potenza
Mariano Santo Hospital, Cosenza
S Giovanni di Dio e Ruggi d'Aragona, Salerno
Civil Hospital, Noale, Venezia
Sacco Hospital
S Gerardo Hospital, Monza, Milano
Civil Hospital, Rovereto, Trento
Molinette Hospital
San Luigi Gonzaga Hospital, Orbassano, Torino
Forlanini Hospital
Instituto Nazionale Ripose e Cura Anziani, Roma
Civil Hospital, Padova
Pneumology, University of Palermo, Palermo
S Vincenzo Hospital, Taormina, Catania
Centro di Riferimento Oncologico, Aviano, Pordenone, Italy
ABSTRACT
PURPOSE: To study the prognostic value for overall survival of baseline assessment of functional status, comorbidity, and quality of life (QoL) in elderly patients with advanced non—small-cell lung cancer treated with chemotherapy.
PATIENTS AND METHODS: Data from 566 patients enrolled onto the phase III randomized Multicenter Italian Lung Cancer in the Elderly Study (MILES) study were analyzed. Functional status was measured as activities of daily living (ADL) and instrumental ADL (IADL). The presence of comorbidity was assessed with a checklist of 33 items; items 29 and 30 of the European Organisation for Research and Treatment of Cancer (EORTC) core questionnaire QLQ-C30 (EORTC QLQ-C30) were used to estimate QoL. ADL was dichotomized as none versus one or more dependency. For IADL and QoL, three categories were defined using first and third quartiles as cut points. Comorbidity was summarized using the Charlson scale. Analysis was performed by Cox model, and stratified by treatment arm.
RESULTS: Better values of baseline QoL (P = .0003) and IADL (P = .04) were significantly associated with better prognosis, whereas ADL (P = .44) and Charlson score (P = .66) had no prognostic value. Performance status 2 (P = .006) and a higher number of metastatic sites (P = .02) also predicted shorter overall survival.
CONCLUSIONS: Pretreatment global QoL and IADL scores, but not ADL and comorbidity, have significant prognostic value for survival of elderly patients with advanced non—small-cell lung cancer who were treated with chemotherapy. Using these scores in clinical practice might improve prognostic prediction for treatment planning.
INTRODUCTION
Non—small-cell lung cancer (NSCLC) is a group of heterogeneous clinical entities with different clinical behaviors and prognoses. As is true for many other types of tumors, the proportion of NSCLC patients aged 70 years or older is constantly increasing in industrialized countries because of the gain in life expectancy observed in the second part of the last century, and this trend is expected to continue in the next decades.1
In addition to classical prognostic factors for advanced NSCLC including performance status (PS) and the extent of disease,2 elderly cancer patients have peculiar characteristics that may affect prognosis. In this regard, a pretreatment geriatric assessment, including evaluation of comorbidity, functional status, depression, cognitive impairment, nutritional status, and social support, has been proposed to assess prognosis and predict toxicity.3-5 However, the advantage of such a comprehensive assessment is probably outweighed by the disadvantage of its poor applicability in clinical practice.
The assessment of comorbidity and the evaluation of functional status are among the most important constituents of a comprehensive geriatric assessment. Comorbidity may be summarized according to several scales.6,7 Functional status refers to the ability of the patient to perform daily functions. Assessment of PS is the most widely used functional score in oncology, however, it has been suggested that this score might underestimate the degree of functional impairment, particularly in the elderly subset of patients.3 The most widely used functional impairment geriatric scales are Katz's basic Activities of Daily Living (ADL)8 and Lawton's9 Instrumental Activities of Daily Living (IADL). Although these geriatric scales may produce additional information on the functional assessment of elderly cancer patients, their prognostic role in elderly patients with advanced NSCLC is unknown.
The Multicenter Italian Lung Cancer in the Elderly Study—01 (MILES-01)10 was a large prospective randomized trial of chemotherapy dedicated to elderly patients with advanced NSCLC. This study showed that polychemotherapy with gemcitabine plus vinorelbine was not more effective than gemcitabine alone and vinorelbine alone. A previous study by the same group of investigators,11 the phase III Elderly Lung Cancer Vinorelbine Italian Study (ELVIS) study, showed that vinorelbine was better than supportive care in elderly patients with advanced NSCLC. Also in that study, we found that the baseline scores of items 29 and 30 of the European Organisation for Research and Treatment of Cancer (EORTC) core questionnaire QLQ-C30 predicted time to dropout from the study; patients with worse scores tended to drop out earlier than patients with higher scores.11
The current study was planned a priori in the MILES protocol to explore the possible prognostic role of ADL, IADL, and comorbidity. Following the reported results of the ELVIS study, we also included quality of life measured with items 29 and 30 of EORTC QLQ-C30 as a covariate of prognostic analysis.
PATIENTS AND METHODS
Patients and Treatment
Patients with advanced NSCLC enrolled onto the MILES study10 were 70 years old or older, had stage IV or IIIB disease with supraclavicular metastatic nodes or malignant pleural effusion, and a baseline PS not worse than 2, according to the Eastern Cooperative Oncology Group (ECOG) scale. The MILES study compared the combination of vinorelbine and gemcitabine with the two drugs given singly. Patients were randomly assigned to receive vinorelbine (30 mg/m2), gemcitabine (1,200 mg/m2), or gemcitabine (1,000 mg/m2) plus vinorelbine (25 mg/m2). All treatments were administered on days 1 and 8 every 3 weeks for six cycles of 21 days. The primary end point of the study was overall survival. Of 707 patients randomly assigned between December 1997 and November 2000, 566 patients (80%) with complete information on baseline ADL, IADL, and quality of life were included in this prognostic analysis.
Global Health Status/Quality of Life
To assess quality of life, the EORTC QLQ-C3012 and the EORTC lung cancer—specific module QLQ-LC1313 were used. In the current analysis, only one score was used, the global health status/quality of life (QoL), calculated with responses to items 29 and 30 of EORTC QLQ-C30. In response to these two items, patients were asked to grade their global health status (item 29) and quality of life (item 30) during the previous week on a scale of 7 points. A raw score was calculated for each patient and linearly transformed in a percent scale ranging from 0 to 100, 0 representing the lowest level of global quality of life and 100 the highest. In this analysis, patients were grouped in three score categories using first and third quartiles as cut points: "better" (scoring > 67%, roughly representing the highest quarter of the distribution), "intermediate" (scoring 43% to 67%, about half of subjects), and "worse" (scoring 42%, representing the lowest quarter of the distribution).
Geriatric Assessment
Concomitant pathologies were scored as absent/present using a predefined list of 33 possible diseases. Comorbidity was summarized by the Charlson score,6 summing up data regarding myocardial infarction, congestive heart failure, peripheral vascular disease, cerebral vascular disease, dementia, chronic obstructive pulmonary disease, connective tissue disease, ulcer disease, mild liver disease and diabetes. The other pathologic conditions (hemiplegia, moderate or severe renal disease, diabetes with organ damage, any other cancer, moderate or severe liver disease, AIDS) used to calculate the Charlson score were not taken into account because they were precluded by exclusion criteria for the study. Consequently, higher scores were rarely attained, and just four categories were used in the analysis (0, 1, 2, 3).
Functional status of elderly patients was measured by ADL and IADL scores that were recorded at baseline, before randomization, by physicians.
ADL8 includes bathing, dressing, using the bathroom, continence, getting up and being able to move around the house, and feeding. For each of the six items, two possible scores were assigned: 0 (dependent) or 1 (independent). Thus, the ADL score for each patient ranged from 0 (unable to perform any activity) to 6 (able to perform all activities). Because of the high prevalence of patients scoring 6, two groups were arbitrarily created for this analysis: fully independent (score 6) and 1 dependency (scores < 6).
IADL9 includes the ability to use the telephone, shopping, food preparation, housekeeping, handyman work, laundry, the ability to get around outside the home, responsibility for own medications, and the ability to handle finances. For each item four responses are available, three representing varying degrees of dependency (all assigned score 0) and one representing full independency (score 1). Some of the explored domains (eg, cooking, washing clothes, and so on) are fully applicable only to women, considering the advanced age of the population. Thus, missing data within the forms were frequent among men. To accommodate this phenomenon, a raw score was calculated considering only questions that had been answered by the patients, on the assumption that missing values were primarily due to inapplicability of the question. Such score was linearly transformed in a percent scale ranging from 0 to 100, 0 representing the lowest level of ability and 100 the highest. For prognostic and correlation analyses, patients were arbitrarily grouped in three score categories: "better" (scoring 100%, roughly representing the best quarter), "intermediate" (scoring 51% to 99%, about half of the subjects), and "worse" (scoring 0% to 50%, representing the worst quarter).
Statistical Methods
Associations between baseline ADL, IADL, and QoL categories and characteristics of patients were studied by contingency tables and the 2 test.
Overall survival was defined as the time elapsed from the date of randomization to the date of death or the date of the last follow-up for patients alive at the end of the study. Multivariate survival analysis was done using the Cox model,14 and was stratified by treatment arm. Because of the high number of events, a simple strategy was undertaken by a single model including all known or potential prognostic factors (age, sex, stage, histotype, number of sites of disease, baseline QoL, ADL, IADL, and Charlson score) and a variable representing institutions by number of patients enrolled (< 10, 10-29, 30) as a possibly confounding covariate. The likelihood ratio test was used to test the contribution of each variable to the model when added last, that is after adjustment for all of the other covariates. P values less than .05 were considered statistically significant. Overall survival curves were drawn by the Kaplan-Meier method.15
RESULTS
Patient Characteristics
Median age of the patients was 74 years (range, 70 to 84 years); 229 patients (40%) were 75 years old or older (Table 1). Men represented 82% of the population. Institutions that enrolled more than 30 patients comprised about one fourth of the patients; those that enrolled between 10 and 29 patients comprised about half the patients.
More patients with stage IV disease than stage III disease were enrolled, representing 69% of the sample (Table 2). Squamous cell carcinoma was the most prevalent histologic type (45% of patients), followed by adenocarcinoma (34%). Patients had a median of three organs affected by cancer. Nineteen percent of patients had a deteriorated baseline PS (ECOG category 2). Approximately 90% of the patients had at least one and approximately 40% had three or more comorbidities; only 11% of patients had no comorbidity. According to the Charlson score, 42% of patients were in the lowest category (score 0).
QoL, ADL, IADL, and Charlson score
Distribution of baseline QoL, ADL, and IADL in the population is illustrated in Figure 1. QoL was distributed symmetrically, with the majority of patients reporting intermediate scores. Conversely, both ADL and IADL distributions were highly skewed, the best score being most frequent (85% and 33% for ADL and IADL, respectively).
PS was significantly correlated with QoL, ADL, and IADL scores. All the scores were worse among patients with PS2 (Table 2; all P values < .0001), whereas Charlson score was only associated with IADL, being lower in patients with higher IADL scores (P = .005).
Overall Survival
Of 566 patients eligible for prognostic analysis, 462 patients (82%) died. Median overall survival for patients was 30 weeks (95% CI, 28 to 34), and 6-month and 1-year probabilities of overall survival were 0.56 and 0.32, respectively.
Results of multivariate analysis are reported in Table 3. After adjusting for the other covariates, QoL and IADL were associated with prognosis (P = .0003 and P = .04, respectively), whereas ADL was not (P = .44). A low PS (ECOG score 2) and the number of metastatic sites also independently predicted worse overall survival rates (P =.006 and P = .02, respectively). Charlson score was not associated with prognosis; the results were superimposible if the total number of comorbidities was used instead of the Charlson score. Kaplan-Meier—estimated overall survival curves for QoL and IADL are shown in Figure 2.
DISCUSSION
A significant amount of both clinical and basic research has focused on the prognostic factors for patients with NSCLC. Although the prognosis of patients with advanced NSCLC is ominous overall, the identification of prognostic factors can be useful, not only for providing important information to the patients, but also for the correct choice of treatment. The latter issue is particularly relevant for elderly patients, because of the concerns about generalizability of treatment effects demonstrated in younger patients16 and poor tolerability of treatments.
Within a secondary analysis of the MILES study, we looked for new tools to predict the prognosis of elderly patients at the time of diagnosis and before chemotherapy treatment. Specifically, we studied the prognostic value of the patient's self-assessment of QoL and physician's assessment of functional scales (ADL and IADL) and comorbidity.
As for comorbidity, we recognize that a limitation of the present study consists of the use of a qualitative yes/no checklist, which does not result in information about the severity of concomitant diseases. This choice was pragmatically based on the principle of reducing the time needed to assess patients at baseline. A similar scale has been used previously by Repetto et al.5 The Charlson score,6 which was used as a summary measure of comorbidity, revealed no prognostic value in the MILES study. Although the potential prognostic role of the Charlson score was limited by the fact that eligibility criteria of the study excluded patients with higher scores, this finding is consistent with those recently reported by Janssen-Heijnen et al 17 showing that among 4,072 patients diagnosed with NSCLC in the Netherlands between 1995 and 1999, the number of comorbidities (collected according to a slightly modified version of the Charlson score) had no prognostic value for overall survival. A possible explanation of the lack of prognostic relevance of comorbidity in advanced lung cancer is reported in a recent paper by Read et al.18 The authors found that among 11,558 cancer patients, concurrent comorbidities had no relevant prognostic impact for groups of patients with the lowest overall survival rates, including 1,005 patients with advanced lung cancer. Whether different and more detailed definitions of comorbidity can produce useful prognostic information in the setting of advanced NSCLC remains to be seen.19,20 However, a study by Piccirillo et al21 of elderly patients with head and neck cancer suggests that general comorbidity indexes (like the Charlson score) perform similarly to disease-specific comorbidity indexes, and both types of scores are only able to weakly predict prognosis.
In contrast with the established prognostic value of ADL in nononcologic geriatric patients,22 baseline ADL had no prognostic value in the MILES population. A possible explanation could be that the prognostic value of ADL, as that of comorbidity,18 may only be truly effective in populations with a life expectancy longer than that of patients with advanced NSCLC. In addition, we should consider that dependencies in ADL represent quite severe deficiencies that probably prevent patients from being considered eligible for chemotherapy and for clinical trials. On the contrary, we found that baseline IADL had an independent prognostic role, that appears mostly relevant for the lower quarter, ie, the worse category. IADL is a quite easy-to-use instrument, but its application is limited by the fact that some domains (eg, cooking, washing clothes, and so on) are not effectively applicable to male patients, particularly if they are elderly. To accommodate this phenomenon, we ignored missing data and calculated a raw score based on available answers; this might reduce reproducibility of the present result.
Another important observation of our study was that baseline self-assessment of QoL, with two simple questions, was the strongest prognostic factor among elderly patients with advanced NSCLC enrolled onto the MILES trial; the major difference being evident between the upper quarter (ie, the better category) and the other categories that appear to have similar prognosis. To our knowledge, the present study reports the largest analysis on the prognostic role of QoL score in advanced NSCLC and the first analysis on the important subset of elderly patients. Indeed, Ganz et al23 reported on the importance of the Functional Living Index—Cancer24 in 40 patients. Montazeri et al25 reported that in a series of 129 patients global QoL measured by the EORTC C-30 questionnaire was significantly lower among the 30 patients who died within 3 months, as compared with the rest of the patients in the study. Langendijk et al26 reported similar results with the EORTC C-30 questionnaire with patients with lung cancer undergoing potentially curative radiation therapy. These results are in slight contrast with the observations of Herndon et al27 on 206 patients enrolled onto the Cancer and Leukemia Group B 8931 trial; they found that although several items of the EORTC C-30 questionnaire (including the overall QoL score) were correlated with prognosis at univariate analysis, only the pain score was retained in the final multivariate model.
In addition to providing crucial prognostic information, QoL assessment may be useful to improve communication with the patient and help the clinician to design tailored supportive treatments based on the correct identification of the overall burden of symptoms, the relative importance given to each of them by the patient, and his or her expectations regarding treatment's efficacy. As an example of poor patient-physician communication, even in the setting of randomized clinical trials, we have recently reported28 that pain measured by the pain scores included in the EORTC C-30 and LC-13 questionnaires is frequently undertreated by physicians, particularly when instrumental staging is negative for bone metastases. Thus, we suggest that the use of QoL instruments in clinical practice could help physicians improve their control of the patient's symptoms. Indeed, the feasibility and utility of a comprehensive assessment of elderly cancer patients, also when based on self-report methodology like QoL questionnaires, has been proven.29
In conclusion, quality of life and functional status assessment, by items 29 and 30 of the EORTC C-30 questionnare and the IADL scale, respectively, could be used in clinical practice as prognostic factors to aid the selection of elderly patients with advanced NSCLC for chemotherapy.
Appendix
List of institutions and coauthors. National Cancer Institute, Napoli: *Medical Oncology B (Cesare Gridelli, Emiddio Barletta, Maria Luisa Barzelloni, Rosario Vincenzo Iaffaioli) and Clinical Trials Unit (Francesco Perrone, Paolo Maione, Ermelinda De Maio, Massimo Di Maio, Gianfranco De Feo). Medical Statistics, Second University of Napoli (Ciro Gallo, Giuseppe Signoriello, Paolo Chiodini). *III Internal Medicine, University Federico II of Napoli (Silvio Cigolari,** Angela Cioffi, Vincenzo Guardasole, Valentina Angelini). *S Carlo Hospital, Potenza (Luigi Manzione, Antonio Rossi, Domenico Bilancia, Domenico Germano). Pneumology V, Monaldi Hospital, Napoli (Francovito Piantedosi, Alfredo Lamberti, Vittorio Pontillo, Luigi Brancaccio). Mariano Santo Hospital, Cosenza (Santi Barbera, Francesco Renda, Francesco Romano). Sacco Hospital, Milan (Elena Piazza, Gabriella Esani, Anna Gambaro). Medical Oncology, Noale—VE (Orazio Vinante, Francesco Rosetti, Giuseppe Azzarello). S Giuseppe Hospital, Milano (Maurizia Clerici, Roberto Bollina, Paolo Belloni). S Maria del Carmine Hospital, Rovereto—TN (Sergio Federico Robbiati, Mirella Sannicolò). Molinette Hospital, Torino (Oscar Bertetto, Libero Ciuffreda, Giuseppe Parello). S Paolo Hospital, Milano (Luciano Frontini, Mary Cabiddu#). S Maria della Misericordia Hospital, Udine (Cosimo Sacco, Angela Sibau). San Lazzaro Hospital, Alba—CN (Gianfranco Porcile, Federico Castiglione, Oliviero Ostellino). Civil Hospital, Padova (Silvio Monfardini, Adolfo Favaretto, Micaela Stefani). San Luigi Gonzaga Hospital, Orbassano—TO (Giorgio Scagliotti, Silvia Novello, Giovanni Selvaggi). Forlanini Hospital, Roma (Filippo De Marinis, Maria Rita Migliorino, Olga Martelli). Medical Oncology, Az Ospedaliera "Bianchi-Melacrino-Morelli", Reggio Calabria (Giampietro Gasparini,? Alessandro Morabito,? Domenico Gattuso). *Experimental Medical Oncology, Oncologic Institute, Bari (Giuseppe Colucci, Domenico Galetta, Francesco Giotta). *Medical Oncology, University of Palermo (Vittorio Gebbia). *La Maddalena Hospital, Palermo (Nicola Borsellino, Antonio Testa). *S Vincenzo Hospital, Taormina—CT (Francesco Ferraù, Emilia Malaponte). Thoracic Surgery, University of Foggia (Matteo A. Capuano, Michele Angiolillo, Francesco Sollitto). Medical Oncology, CRO, Aviano—PN (Umberto Tirelli, Alessandra Bearz, Simona Spazzapan). Medical Oncology, University of Messina (Vincenzo Adamo, Giuseppe Altavilla, Antonino Scimone). Pneumology, University of Palermo (Mario Spatafora, Maria Raffaella Hopps, Francesco Tartamella). G. Rummo Hospital, Benevento (Giovanni Pietro Ianniello, Vincenza Tinessa). S Luigi and S.S. Currò Gonzaga Hospital, Catania (Giuseppe Failla, Roberto Bordonaro). Chemotherapy, University of Palermo (Nicola Gebbia, Maria Rosaria Valerio). *S Maria Goretti Hospital, Latina (Modesto D'Aprile, Enzo Veltri), Latina. Medical Oncology, University of Perugia (Maurizio Tonato, Samir Darwish). *Cardarelli Hospital, Campobasso (Sante Romito, Francesco Carrozza). S Gerardo Hospital, Monza—MI (Sandro Barni,# Antonio Ardizzoia). USSL 33, Rho—MI (Giuliana Mara Corradini, Gianfranco Pavia). *Civil Hospital, Avellino (Mario Belli, Giuseppe Colantuoni). S Chiara Hospital, Trento (Enzo Galligioni, Orazio Caffo). Medical Oncology, Spedali Riuniti, Bergamo (Roberto Labianca, Antonello Quadri). Medical Oncology, University La Sapienza, Roma (Enrico Cortesi, Giuliana D'Auria). Civil Hospital, Legnano— MI (Sergio Fava, Anna Calcagno). S Carlo Borromeo Hospital, Milano (Gino Luporini, M. Cristina Locatelli). S Maria Hospital, Terni (Francesco Di Costanzo, Silvia Gasperoni). Serbelloni Hospital, Gorgonzola—MI (Luciano Isa, Paola Candido). USSL 15, Camposampiero—PD (Fernando Gaion, Giovanni Palazzolo). *Miulli Hospital, Acquaviva delle Fonti—BA (Giuseppe Nettis, Anselmo Annamaria). *Medical Oncology II, "Regina Elena" Institute, Roma (Massimo Rinaldi, Massimo Lopez). S Martino Hospital, Genova (Raffaella Felletti, Giorgio Bernabò Di Negro). *Civil Hospital, Polla—SA (Nestore Rossi, Antonio Calandriello). San Gennaro Hospital, Napoli (Luigi Maiorino). S Croce Hospital, Fano—PS (Rodolfo Mattioli). S Giovanni Hospital, Torino (Alfredo Celano). S Bortolo Hospital, Vicenza (Stefania Schiavon). Oncology, Monaldi Hospital, Napoli (Alfonso Illiano). Cottolengo Hospital, Torino (Carlo Alberto Raucci). *Oncologic Center, Catania (Michele Caruso). Medical Oncology, University of Milano (Paolo Foa||). Medical Oncology, Biomedical Campus, Roma (Giuseppe Tonini). Thoracic Surgery, Ascalesi Hospital, Napoli (Carlo Curcio). Civil Hospital, Treviglio—BG (Marina Cazzaniga). Pneumology, Spedali Riuniti, Bergamo. Medical Oncology I, IST, Genova. *Fatebenefratelli Hospital, Benevento. *Medical Oncology, University of Cagliari. Businco Hospital, Cagliari. Agnelli Hospital, Pinerolo— TO. SS Trinità Hospital, Sora—FR. S Andrea Hospital, Vercelli. Civil Hospital, Gorizia. Medical Oncology, University of Sassari. Civil Hospital, Bolzano. Fortunato Hospital, Rionero in Vulture—PZ. *Da Procida Hospital, Salerno. C Cantù Hospital, Abbiategrasso—MI. Pugliese Ciaccio Hospital, Catanzaro. Civil Hospital, Rovigo. S Maria delle Grazie Hospital, Pozzuoli—NA. Civil Hospital, S Felice a Cancello—CE. *Galateo Hospital, S.Cesareo—LE. Civil Hospital, Lagonegro—PZ. *Civil Hospital, Sciacca—AG.
NOTE: (*) denotes Institutions that participate in the activities of the Gruppo Oncologico Italia Meridionale; () S Giuseppe Moscati Hospital, Avellino; ()DaProcida Hospital, Salerno; () S Gerardo Hospital, Monza; (||) S Paolo Hospital, Milano; (?) S Filippo Neri Hospital, Roma; (#) Civil Hospital, Treviglio (BG); (**) S Giovanni di Dio e Ruggi d'Aragona, Salerno; () Monaldi Hospital, Napoli.
Authors' Disclosures of Potential Conflicts of Interest
Although all authors completed the disclosure declaration, the following authors or their immediate family members indicated a financial interest. No conflict exists for drugs or devices used in a study if they are not being evaluated as part of the investigation. For a detailed description of the disclosure categories, or for more information about ASCO's conflict of interest policy, please refer to the Author Disclosure Declaration and the Disclosures of Potential Conflicts of Interest section in Information for Contributors.
Acknowledgment
We thank Federika Crudele, Giuliana Canzanella, Fiorella Romano, and Assunta Caiazzo for data management and secretarial assistance; Alfonso Savio for hardware and software assistance; and the Gruppo Oncologico Italia Meridionale (GOIM) for promoting the study among its associated centers.
NOTES
Supported in part by Associazione Italiana per la Ricerca sul Cancro (AIRC), Clinical Trials Promoting Group (CTPG), and Gruppo Italiano di Oncologia Geriatrica (GIOGer). P.M. is the recipient of an AIRC fellowship.
Presented in part at the 38th Annual Meeting of the American Society of Clinical Oncology, Orlando, FL, May 18-21, 2002 (poster).
Authors' disclosures of potential conflicts of interest are found at the end of this article.
REFERENCES
Ries LAG, Eisner MP, Hankey BF, et al: SEER Cancer Statistic Review, 1973-1998. Bethesda, MD, National Cancer Institute, 2001
Brundage MD, Davies D, Mackillop WJ: Prognostic factors in non-small cell lung cancer: A decade of progress. Chest 122:1037-1057, 2002
Inouye SK, Peduzzi PN, Robison JT, et al: Importance of functional measures in predicting mortality among older hospitalized patients. JAMA 279:1187-1193, 1998
Balducci L: Geriatric oncology: Challenge for the new century. Eur J Cancer 36:1741-1754, 2000
Repetto L, Fratino L, Audisio A, et al: Comprehensive geriatric assessment adds information to Eastern Cooperative Oncology Group Performance status in elderly cancer patients: An Italian Group for Geriatric Oncology study. J Clin Oncol 20:494-502, 2002
Charlson ME, Pompei P, Ales K, et al: A new method of classifying prognostic comorbidity in longitudinal studies: Development and validation. J Chronic Dis 40:373-383, 1987
Satariano WA, Ragland DR: The effect of comorbidity on 3-year survival of women with primary breast cancer. Ann Intern Med 120:104-110, 1994
Katz S: Assessing self maintenance: Activities of daily living, mobility and instrumental activities of daily living. J Am Geriatr Soc 31:721-727, 1983
Lawton MP, Brody EM: Assessment of older people: Self-maintaining and instrumental activities of daily living. Gerontologist 9:179-186, 1969
Gridelli C, Perrone C, Gallo C, et al: Chemotherapy for elderly patients with advanced non-small cell lung cancer: The MILES (Multicenter Italian Lung Cancer in the Elderly Study) phase 3 randomized trial. J Natl Cancer Inst 95:362-372, 2003
Elderly Lung Cancer Vinorelbine Italian Study Group: Effects of vinorelbine on quality of life and survival of elderly patients with advanced non-small-cell lung cancer. J Natl Cancer Inst 91:66-72, 1999
Aaronson NK, Ahmedzai S, Bergman B, et al: The European Organization for Research and Treatment of Cancer QLQ-C30: A quality of life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 85:365-376, 1993
Bergman B, Aaronson NK, Ahmedzai S, et al: The EORTC QLQ-LC13: A modular supplement to the EORTC core quality of life questionnaire (QLQ-C30) for use in lung cancer clinical trials. Eur J Cancer 30A:635-642, 1994
Cox DR: Regression models and life tables. J R Stat Soc B 34:187-220, 1972
Kaplan EL, Meier P: Non parametric estimation from incomplete observation. J Am Stat Assoc 53:457-481, 1958
Perrone F, Gallo C, Gridelli C: Re: Cisplatin-based therapy for elderly patients with advanced non-small-cell lung cancer: Implications of Eastern Cooperative Oncology Group 5592—A randomized trial. J Natl Cancer Inst 94:1029-1030, 2002 (letter)
Janssen-Heijnen MLG, Smulders S, Lemmens VEPPP, et al: Effect of comorbidity on the treatment and prognosis of elderly patients with non-small cell lung cancer. Thorax 59:602-607, 2004
Read WL, Tierney RM, Page NC, et al: Differential prognostic impact of comorbidity. J Clin Oncol 22:3099-3103, 2004
Piccirillo JF, Tierney RM, Costas I, et al: Prognostic importance of comorbidity in a hospital-based cancer registry. JAMA 291:2441-2447, 2004
Repetto L, Venturino A, Fratino L, et al: Geriatric oncology: A clinical approach to the older patient with cancer. Eur J Cancer 39:870-880, 2003
Piccirillo JF, Spitznagel EL, Vermani N, et al: Comparison of comorbidity indices for patients with head and neck cancer. Med Care 42:482-486, 2004
McCusker J, Bellavance F, Cardin S, et al: Detection of older people at increased risk of adverse health outcomes after an emergency visit: The ISAR screening tool. J Am Geriatr Soc 47:1229-1237, 1999
Ganz PA, Lee JJ, Siau J: Quality of life assessment: An independent prognostic variable for survival in lung cancer. Cancer 67:3131-3135, 1991
Schipper H, Clinch J, McMurray A, et al: Measuring the quality of life of cancer patients: The Functional Living Index-Cancer—Development and validation. J Clin Oncol 2:472-483, 1984
Montazeri A, Milroy R, Hole D, et al: Quality of life in lung cancer patients as an important prognostic factor. Lung Cancer 31:233-240, 2001
Langendijk H, Aaronson NK, de Jong JM, et al: The prognostic impact of quality of life assessed with the EORTC QLQ-C30 in inoperable non-small cell lung carcinoma treated with radiotherapy. Radiother Oncol 55:19-25, 2000
Herndon JE, Fleishman S, Kornblith AB, et al: Is quality of life predictive of the survival of patients with advanced non-small cell lung carcinoma? Cancer 85:333-340, 1999
Di Maio M, Gridelli C, Gallo C, et al: Prevalence and management of pain in Italian patients with advanced non-small-cell lung cancer. Br J Cancer 90:2288-2296, 2004
Ingram SS, Seo PH, Martell RE, et al: Comprehensive assessment of the elderly cancer patient: The feasibility of self-report methodology. J Clin Oncol 20:770-775, 2002(Paolo Maione, Francesco P)