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Ann Thorac Surg 2006;81:1021-1027
© 2006 The Society of Thoracic Surgeons

Original article: General thoracic

Predicting Postrecurrence Survival Among Completely Resected Nonsmall-Cell Lung Cancer Patients

Brent A. Williams, MS a , Hiroshi Sugimura, MD b , Chiaki Endo, MD b , Francis C. Nichols, MD c , Stephen D. Cassivi, MD c , Mark S. Allen, MD c , Peter C. Pairolero, MD c , Claude Deschamps, MD c , Ping Yang, MD, PhD b , *

a Division of Biostatistics, Mayo Clinic College of Medicine, Rochester, Minnesota
b Division of Epidemiology and Cancer Center, Mayo Clinic College of Medicine, Rochester, Minnesota
c Division of General Thoracic Surgery, Mayo Clinic College of Medicine, Rochester, Minnesota

Accepted for publication September 9, 2005.

* Address correspondence to Dr Yang, Department of Health Sciences Research, Mayo Clinic Cancer Center, 200 First St SW, Charlton 6-261, Rochester, MN 55905 (Email: yang.ping{at}mayo.edu).


   Abstract
Top
 Abstract
Introduction
 Patients and Methods
 Results
 Comment
 Acknowledgments
 References
 
BACKGROUND: Survival after recurrence subsequent to complete resection of nonsmall-cell lung cancer (NSCLC) has been considered a multifactorial process dependent on demographic, clinical, biological, and treatment characteristics. This study sought to quantify the prognostic effects of these characteristics on postrecurrence survival.

METHODS: Three hundred ninety NSCLC patients who underwent complete resection and subsequently had recurrent cancer were studied. The associations between characteristics of both the initial and recurrent disease with postrecurrence survival were evaluated by Cox proportional hazards models. A multivariable Cox model determined those factors most strongly associated with postrecurrence survival . A simple algorithm based on this model facilitates estimating risk of postrecurrence mortality, as quantified by risk score points.

RESULTS: The factors most strongly associated with postrecurrence survival were performance status at recurrence (3 or 4, 4.2 points; 2, 2.8 points; and 1, 1.5 points), symptoms at recurrence (3.6 points), liver recurrence (2.3 points), initial lung cancer stage IIB or worse (1.8 points), and multiple recurrences (1.0 points). Based on these factors, patients were stratified as low risk (4.0 or fewer total points), moderate-low risk (4.1 to 6.1 points), moderate-high risk (6.1 to 8.0 points), and high risk (more than 8.0 points), with 12-month survival of 75%, 51%, 25%, and 9%, respectively. Postrecurrence survival was significantly different across groups (p < 0.01).

CONCLUSIONS: The proposed prediction instrument offers clinicians a succinct tool for rapidly evaluating mortality risk after recurrence. The characteristics comprising this instrument can be easily ascertained and measured, making it of potential clinical value.


   Introduction
Top
 Abstract
 Introduction
Patients and Methods
 Results
 Comment
 Acknowledgments
 References
 
Despite the curative intent of complete resection of nonsmall cell lung cancer (NSCLC), recurrence has been reported to be 20% to 85%, depending primarily on disease stage and length of follow-up [1–11]. Among patients having a recurrence, reported rates of location are 22% to 50% for isolated local recurrence, 48% to 78% for isolated distant recurrence, and 3% to 20% for simultaneous local and distant recurrence [1–3, 5–8, 10–16]. Survival after recurrence has been reported as a multifactorial process dependent on demographic, disease, biological, and treatment characteristics of both the initial and recurrent malignancies [6, 8, 10, 11, 13, 16–20]. Research on postrecurrence survival has focused predominantly on the effects of treatment, with much less attention given to the many additional potentially prognostic factors. Published reports evaluating predictors of postrecurrence survival are limited in generalizability owing to their small cohorts and concomitant low statistical power to adequately evaluate even modest numbers of predictors. In addition, a few of these studies have evaluated patients with both local and distant recurrence [6, 8, 10, 11], with additional studies confined to either local [13, 16, 18, 19] or distant [20] recurrence. None of these studies attempted to risk-stratify patients with respect to mortality after recurrence.

A large study elucidating risk factors for postrecurrence mortality with simultaneous risk stratification is warranted. The infrastructure currently in place for recruiting and subsequently following lung cancer patients at Mayo Clinic Rochester provides an abundant resource for conducting such a study [21, 22]. A recent study conducted by our group reported the effects of treatment and other characteristics on postrecurrence survival [23]. The current investigation attempts to augment these findings by developing a predictive model to facilitate the risk stratification of patients with respect to postrecurrence mortality.


   Patients and Methods
Top
 Abstract
 Introduction
 Patients and Methods
Results
 Comment
 Acknowledgments
 References
 
The Mayo Clinic Epidemiology and Genetics of Lung Cancer Research Program has enrolled and prospectively followed patients either diagnosed with or treated for lung cancer at Mayo Clinic, Rochester, Minnesota, since its inception in 1997. The Mayo Foundation Institutional Review Board approved this study before any patient enrollment. Between January 1, 1997, and December 31, 2001, 4,673 patients (4,155 NSCLC, 518 small-cell lung cancer) have been enrolled. Procedures for identifying and following lung cancer patients enrolled in this program have been previously described [21–24]. Among the 4,155 NSCLC patients enrolled in the program, 1,361 (33%) received a complete resection with curative intent. The presence of recurrent disease was identified from Mayo Clinic (by medical records or follow-up questionnaires) and outside sources (by correspondence letters or copied medical records). Diagnosis was confirmed through physical examination and diagnostic imaging of lesions when possible. Only patients for whom presence or absence of recurrent cancer could be determined with virtual certainty through 2003 were included in this study. Using this criterion, 1,073 of the original 1,361 complete resections comprised the final patient cohort [23]. We have used a combination of routine research follow-up and nonuniform clinical surveillance to maximize the data collection. The presence of symptoms was determined by a thoracic surgeon (Hiroshi Sugimura) based on clinical judgment according to information available in medical records and self-reported on follow-up questionnaires. Only a new or worsening symptom that led to or accompanied the diagnosis of recurrence was considered as a symptomatic recurrence.

For patients with a recurrent cancer, factors related to both the initial lung and subsequent cancers were identified. Demographic variables included age at initial lung cancer diagnosis and at recurrence, sex, and smoking history before NSCLC, including smoking intensity and duration. Characteristics of the initial lung cancer included stage, performance status, symptoms (cough, sputum production, chest pain, and so forth), histology, and tumor grade of differentiation [25–27]. Characteristics of the subsequent cancer included years disease free, performance status, symptoms both local and distant (neurologic deficit, bone pain, general or systemic symptoms such as drastic loss of appetite or weight, and so forth), single versus multiple recurrence (defined as having two or more noncontiguous recurrences within a single or multiple organs), site of recurrence, and treatment.

The primary endpoint in this study was survival after diagnosis of recurrent cancer. Survival was defined as the time in days from the date of recurrent cancer diagnosis to death or the last date the patient was known to be alive. Patients known to be alive at last contact were censored. Cox proportional hazards regression models were developed to determine the association between each of the aforementioned variables and postrecurrence survival. Relative risks and 95% confidence intervals (CI) are reported across variable categories, and differences in survival across categories were tested. Continuous variables were grouped for ease of analysis into approximate quartiles before determining the variable's association with survival. All reported characteristics were considered in a multivariable Cox model to determine which demonstrated the strongest associations with survival. A forward stepwise selection procedure was implemented with a p value threshold of 0.05 for inclusion in the final model. Treatments for recurrence, as defined in our earlier report, were included as adjustor variables in all Cox models [23]. Relative risks and 95% CIs are reported for those variables included in the final model.

The final multivariable model was converted to a risk score for postrecurrence mortality by the following steps: (1) the variable with the smallest regression coefficient in the model was assigned 1.0 risk score points; (2) risk score points were assigned to all other variables in the model by dividing their respective regression coefficients by the smallest coefficient in the model—this quotient rounded to the nearest tenth is the risk score point assignment for that variable; and (3) a total risk score was calculated for every patient by adding the risk score points assigned to each variable in the model. The set of total risk scores were divided into four groups, and the Kaplan-Meier survival curves for each juxtaposed in order to qualitatively assess the risk score's ability to discriminate between patients at high and low risk of mortality. The discriminating ability of the risk score model was measured quantitatively by the c-statistic [28]. Possible c-statistic values range from 0.5 (no discriminatory ability) to 1.0 (perfect discriminatory ability). Criteria for judging the discriminatory strength of c-statistics have been reported [29]. In general, lower c-statistics will result when the sources of variability associated with the outcome are not well known or difficult to quantify.


   Results
Top
 Abstract
 Introduction
 Patients and Methods
 Results
Comment
 Acknowledgments
 References
 
Among 1,073 NSCLC patients who underwent a complete resection with curative intent, 445 (41.5%) were identified as having recurrent disease during the study follow-up period. Fifty-five patients who had a recurrence had to be excluded from this analysis because of a lack of information on date of recurrence, anatomical site, or treatment for recurrence. A comparison between these 55 patients and the remaining 390 patients with complete data on lung cancer recurrence showed that age, state of residence, smoking status (current smoker or not), and disease stage were very comparable at the time of primary lung cancer diagnosis. However, more men (78%) were among the 55 patients than among the 390 patients (58%). Among the 390 patients, 79 (20%) had only local recurrence, 249 (64%) only distant recurrence, and 62 (16%) had recurrences in both local and distant organ sites. The median time from resection to recurrence diagnosis was 11.5 months (25th, 75th percentiles: 6.0, 20.7). Overall median postrecurrence survival was 8.1 months. Estimated survival at 12 and 24 months was 37% and 17%, respectively.

Characteristics of the initial lung cancer portending detrimental effects on postrecurrence survival included advanced stage, worse performance status, presence of symptoms, squamous cell type, and higher grade (Table 1). Recurrent cancer characteristics demonstrating negative effects on postrecurrence survival included shorter disease-free interval, worse performance status, presence of symptoms, multiple recurrences, and nonlung recurrences, particularly in the bone or liver (Table 2).


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  		Table 1. Associations Between Initial Lung Cancer Characteristics and Postrecurrence Mortality
 

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  		Table 2. Associations Between Recurrent Cancer Characteristics and Postrecurrence Mortality
 
The final multivariable model of risk factors for postrecurrence survival with corresponding risk score points is shown in Table 3. This model included four characteristics related to the recurrence (performance status, presence of symptoms, liver recurrence, number of recurrences) and one characteristic of the initial lung cancer (stage). Performance status and stage were grouped as shown based on empirical findings. Risk score points are assigned as shown for each of the five listed factors, with a total risk score calculated per patient as the sum of the risk score points for all five factors. Table 4 shows the risk score calculations for the 10 most commonly observed combinations of factors in our patient population. For instance, as shown in the first row of Table 4, an individual with stage IIB disease or higher lung cancer (1.8 risk score points), with symptoms at recurrence (3.6), with a single recurrence (0.0), without liver recurrence (0.0), and a performance status at recurrence of one (1.5 points) would be assigned a risk score of 6.9 points (risk score = 1.8 + 3.6 + 0.0 + 0.0 + 1.5 = 6.9).


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  		Table 3. Multivariable Predictors of Postrecurrence Survival and Risk Score (RS) Point Assignments
 

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  		Table 4. Ten Most Commonly Observed Combinations of Risk Factors Among Patients With Recurrence
 
The mean ± SD for the total risk score was 6.0 ± 2.6. Risk score groups were created empirically as follows: (1) risk score of 4.0 or less (low risk); (2) risk score of 4.1 to 6.0 (moderate-low); (3) risk score of 6.1 to 8.0 (moderate-high); and (4) risk score greater than 8.0 (high). Median survival across the four groups was 21.0, 12.0, 6.4, and 3.1 months for low, moderate-low, moderate-high, and high-risk groups, respectively. The estimated 12-month survival across the groups was 75%, 51%, 25%, and 9%, respectively; and the estimated 24-month survival was 45%, 20%, 11%, and 2%, respectively (Fig 1). The c-statistic for the risk score model was 0.70.


Figure 1
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  		Fig 1. Postrecurrence survival by risk score (RS) group.

 
Table 5 presents the treatment modalities across the four risk score groups as defined above. As expected, the higher risk scores were associated with fewer patients undergoing surgical resection or receiving combined chemotherapy and radiation therapy, and a higher likelihood of receiving no treatment. In general, receiving treatment was associated with a lower relative risk of postrecurrence mortality than no treatment across all four risk score groups (Fig 2). Specifically, using the no-treatment group as the reference (relative risk at 1.0), patients with a risk score below 4.0 experienced a more than 70% (95% CI: 10% to 80%) reduction in postrecurrence mortality risk with surgical resection; patients with a risk score above 8.0 experienced a more than 60% (95% CI: 10% to 80%) reduction after receiving chemotherapy; but patients with a risk score of 6 to 8 experienced no survival benefit after receiving radiation therapy.


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  		Table 5. Treatment Modalities Across Risk Score (RS) Groups Among Patients With Complete Resection for Nonsmall Cell Lung Cancer a
 

Figure 2
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  		Fig 2. Relative risks (RR) for treatment across risk score groups among patients who had complete resection for nonsmall-cell lung cancer. (Circles = surgery; squares = surgery plus chemo/radiotherapy; diamonds = chemotherapy; triangles = chemotherapy plus radiotherapy; asterisk = radiotherapy.)

 

   Comment
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Comment
Acknowledgments
 References
 
Our investigation of an extensive collection of potential risk factors for postrecurrence mortality after a complete resection for NSCLC included nearly twice as many subjects as previous studies considering both local and distant recurrences, permitting more rigorous investigation of risk factors related to both the initial lung cancer and subsequent recurrence. Our prior analysis [23] identified several characteristics, including therapies for both the initial lung and recurrent cancers, associated with postrecurrence survival. In light of the ultimate goal of creating a meaningful risk stratification instrument, the current investigation was limited to risk factors for postrecurrence mortality. The proposed prediction instrument offers clinicians a succinct tool for rapidly evaluating individual mortality risk, summarized by a single easy-to-calculate numerical value. This value should add incremental prognostic information beyond the subjective assessment of the treating clinician.

Our results support specific findings from prior studies, yet also offer a unique set of predictors that contribute substantial information toward the prognostic process. Our final list of five predictors can be divided into three broad categories: severity of primary lung cancer (stage), severity of recurrent disease (performance status, symptoms, number of recurrences), and location of recurrent disease (liver). The implications of each on postrecurrence mortality risk are discussed.

Severity of Primary Lung Cancer
Stage
The prognostic effect of initial lung cancer stage on survival after recurrent cancer is not well understood. Advanced stage of the initially resected NSCLC has been shown to be associated with increased rates of recurrence and shortened recurrence-free intervals [5, 6, 9, 10, 13, 14, 17, 20], implying its probable utility as a marker of tumor aggressiveness or occult disease at resection. The association between stage and postrecurrence survival has been demonstrated by some authors, with advanced stage showing a 30% to 90% increased risk of mortality [6, 10, 20].

Severity of Recurrent Disease
Performance status
Performance status has been long established as a predictor of mortality in lung [4, 25] and other cancers, so our finding of performance status at recurrence being strongly predictive of postrecurrence survival was not unexpected. This result supports two recent studies by Hotta and colleagues [18] (adjusted relative risk = 11.9 for performance status 2 to 4 versus 0 or 1, p = 0.04) and Westeel and coworkers [11] (adjusted relative risk = 1.75 for performance status 3 or 4 versus 0 to 2, p = 0.01), who assessed the prognostic capacity of performance status at the time of recurrence. The incremental escalations in risk observed for increasing performance status scores were also a predictable result.

Symptoms
Our study found a more than twofold increase in mortality risk associated with the presence of symptoms at recurrence, which supports two studies reporting significant or near significant adverse effects of symptoms in patients with local or distant recurrence, or both [10, 11]. The presence of somatic symptoms serves as a logical indicator for more advanced disease and cancer-related cachexia, and hence a presage for premature mortality [30, 31]. Empirical findings from a recent study demonstrated strong associations between symptoms and both advanced disease and worse survival [30]. Tammemagi and colleagues [30] reported that lung cancer patients with any adverse symptoms had more stage III or IV disease (78% versus 53%) and shorter median survival (0.6 versus 1.5 years) than patients with no adverse symptoms. This increased mortality risk among symptomatic patients persisted after adjusting for potential confounders (hazard ratio = 1.89, p < 0.01).

Number of recurrences
The presence of multiple recurrences serves as an additional indicator of advanced disease and justifiably carries a clear disadvantage with regard to postrecurrence survival compared with isolated recurrence. In a study of 118 completely resected NSCLC patients with recurrence at distant organs, Yoshino and colleagues [20] also observed appreciably worse survival at 2 years in patients with multiple metastases (5% versus 17%), but this result was not statistically significant (p = 0.30).

Location of Recurrent Disease
Liver
In our simultaneous comparison of the most prevalent recurrence sites including adrenal gland, bone, brain, liver, lung, and mediastinum, liver recurrence was the only site found to be significantly associated with worse postrecurrence survival in the final model. Three recent studies in patients with terminal cancer at various locales have reported accelerated mortality in patients who developed liver metastasis [31–33]. Among brain, lung, liver, bone, lymph nodes, visceral, and skin metastasis, Vigano and associates [31] found liver metastasis demonstrated the worst survival.

Other Predictors From Prior Studies
Additional variables judged predictive of postrecurrence survival in several prior studies but judged to be not significantly associated with survival in the current investigation are disease-free interval, sex, age, and neoadjuvant and adjuvant therapies for the initial lung cancer. Walsh and coworkers [10] characterized disease-free interval as an "indirect measure of a patient's tumor biology and aggressiveness," so, predictably, longer disease-free interval has been reported in several studies to be associated with prolonged survival after recurrence [8, 16, 17]. Our results and those of others [6, 8, 17, 20] demonstrate the strong correlation between initial stage and disease-free interval, with higher stages typically resulting in shorter disease-free intervals. In our multivariable analysis, however, disease-free interval was not significantly associated with postrecurrence survival owing in part to its association with stage. Finally, the use of neoadjuvant chemotherapy (13%) or adjuvant radiation (14%), or both, was not highly prevalent, and our consideration of only "risk factors" for inclusion in the model precluded the possible addition of neoadjuvant and adjuvant therapies for the initial lung cancer into the final model. From a statistical perspective, the final model reports the treatment-adjusted effects of the risk factors. That is, the estimated relative risks convey the residual elevation in mortality risk associated with the particular characteristic after receiving treatment.

Limitations
A limitation of this study was our inability to procure adequate follow-up information on a subset of patients (21%) who had undergone complete resection. That could introduce bias into our study if patients without adequate follow-up have substantially different recurrence patterns and postrecurrence survival than the study sample. A second limitation was the lack of uniformity in screening for cancer recurrence. Follow-up visits were conducted at various institutions with unique methods and timing of follow-up, presenting a drawback of an observational study such as ours in which routine clinical surveillance for lung cancer recurrence was not standard practice. Thirdly, external validation of the proposed prognostic model in another patient population was not accomplished. Quantitative criteria such as c-statistics for judging the prognostic ability of a model will often be superior in the cohort used to develop the model compared with a validation cohort [34]. Future studies will be able to measure the degree of overoptimism in the current model. Our modest c-statistic (0.70) suggests the presence of other sources of variability in postrecurrence survival; future studies should attempt to identify these sources. Finally, our cohort consists of predominantly Caucasian patients, reflecting the geographic location of our institution, so these results should be validated in cohorts with more ethnic diversity.


   Acknowledgments
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Comment
 Acknowledgments
References
 
The authors would like to thank Susan Ernst for her technical assistance with this manuscript. We also would like to acknowledge Jason Wampfler and Joel Worra for their kind help in generating needed tables and figures. This work was supported by Grants NIH CA80127, NIH CA84354, and NIH CA77118 (Dr Yang) from the US National Cancer Institute and Mayo Foundations Funds.


   References
Top
 Abstract
 Introduction
 Patients and Methods
 Results
 Comment
 Acknowledgments
 References
 

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