Validation of the Functional Assessment of Cancer Therapy—Lung Symptom Index-12 (FLSI-12)
Introduction
The assessment of patient-reported outcomes (PROs) such as symptoms of disease, complications of therapy, and other aspects of health-related quality of life (HRQL) are becoming an integral part of clinical trials of advanced lung cancer. Proper interpretation of clinical trials in advanced cancer often requires assessment of HRQL, including disease-related symptoms. Recently, regulatory authorities have expressed cautious interest in such patient-reported outcomes, with concern expressed regarding the interpretability and relevance of scores from multi-domain instruments. Focused symptom measures have been suggested [1].
Clinical researchers now have a number of standardized assessment options available to them. Two comprehensive measurement systems, that of the European Organization for Research and Treatment of Cancer (EORTC) and the Functional Assessment of Cancer Therapy (FACT), have developed modular approaches to assessing PROs in various cancer sites. The EORTCs core QLQ-C30 [2] is a general cancer measure that is often augmented by the disease-specific LC13 [3] in lung cancer clinical trials. Likewise, the FACT-General measure (FACT-G) [4] is often administered with the disease-specific Lung Cancer subscale (LCS) in lung cancer clinical trials. Together the FACT-G and LCS make up the total FACT-Lung (FACT-L) [5]. Both the EORTC and FACT-Lung modules provide comprehensive assessments of lung cancer symptoms, treatment-related complications (i.e., toxicities), and other functional aspects of HRQL. Both have also been frequently used in lung cancer clinical trials [6], [7] including those of novel targeted therapeutic agents [8]. However, regulatory agencies such as the US Food and Drug Administration (FDA) have grappled with the interpretability of multidimensional HRQL measures as they relate to approvable product label terminology. This concern has led the FDA to draft a guidance document recommending among other things the use of simpler, more targeted symptom assessments, especially in instances where a symptom-focused label claim is ultimately desired for a medical product [1]. Given this, there may be merit in developing and validating simplified assessments of advanced lung cancer symptoms for use in clinical research.
Targeted measures of lung cancer symptoms have been used in clinical lung cancer studies. The Lung Cancer Symptom Scale (LCSS) [9] is a brief measure that focuses entirely on common symptoms of lung cancer including: appetite loss, fatigue, cough, dyspnea, pain, hemoptysis, symptom distress, activity level limitations, and overall quality of life. While psychometrically sound and easy to administer, the LCSS contains no direct measurement of side effects or other complications associated with treatment. Minimally important score differences are also currently unavailable for this measure. Another brief and targeted measure is the previously mentioned LCS of the FACT-L [5]. It too focuses exclusively on symptoms of lung cancer namely: breathing difficulty, weight loss, clarity of thought, coughing, appetite loss, and tightness in chest. It is also psychometrically sound and easy to administer. A minimally important score difference has been estimated for the LCS [10] making it particularly attractive for the clinical trials setting.
While certainly useful as a stand-alone measure, the utility of the LCS could perhaps be enhanced with the addition of a finite set of lung cancer relevant items. In a recent survey of physicians and nurses at 17-member institutions of the National Comprehensive Cancer Network (NCCN), several “priority” symptoms were identified as being important targets of therapy across a range of advanced cancers including lung [11]. Among those issues not currently represented in the LCS were fatigue, pain, nausea, and contentment with quality of life. Furthermore, since documenting patient tolerability to treatment can be as important as documenting treatment efficacy, there may also be added value in incorporating an overall assessment of treatment side effects. Items assessing all of these issues are available in the “core” FACT-G measure. Hence, our interest in this analysis was to take the seven items of the base LCS measure and add five items from the FACT-G that address the expert-derived symptom targets and attention to overall side effect burden. We tested this FACT Lung Symptom Index-12 (FLSI-12) in a sample of advanced lung cancer patients undergoing treatment. Our primary objective was to test the psychometric utility of the revised measure (i.e., reliability, validity, and responsiveness to change over time). A secondary objective was to estimate the minimally important difference (MID) of the scale.
Section snippets
Patients and procedure
From December 2002 through 2004, we enrolled 92 advanced-stage lung cancer patients into a prospective observational study of patient-reported health status. All patients were recruited from the Kellogg Cancer Care Center (KCCC) of Evanston Northwestern Healthcare (Evanston, Highland Park, and Glenbrook Hospitals). Eligibility criteria included: (1) newly diagnosed or recurrent stages III or IV non-small cell lung cancer (NSCLC) or extensive-stage small cell lung cancer (SCLC); (2) initiation
Sample description
Baseline socio-demographic and clinical characteristics of the sample are shown in Table 3. One of the 92 lung cancer patients enrolled was subsequently deemed ineligible; hence data from 91 patients were analyzed. Median age of patients was 70.5 years, most were white (90%) and female (54%). The sample was largely diagnosed with stage IV NSCLC. Median time since diagnosis was a little over 1 month. Most patients rated themselves as having good performance status (PS) at the study outset (80%
Discussion
Our expanded version of the original LCS-7, the FLSI-12, performed quite well in a sample of advanced-stage lung cancer patients followed prospectively after treatment. The index had excellent internal reliability, showed convergence with physical and functional domains of HRQL, and demonstrated concurrent validity. Baseline index scores were able to differentiate patient groups with better versus worse health status or prognostic features. The FLSI-12 was also sensitive to changes in clinical
Conflict of interest
None declared.
Acknowledgements
Funding for this manuscript was provided by Bristol Myers Squibb Company. The sponsor had no role in the study design, collection, analysis or interpretation of data, drafting of the manuscript, or decision to submit the manuscript for publication.
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