Non–small cell lung cancer in never- and ever-smokers: Is it the same disease?

Abstract

Objectives:

To investigate differences in presentation, pathology, and outcomes after resection of non–small cell lung cancer (NSCLC) in never-smokers versus ever-smokers.

Methods:

From January 2006 to July 2016, 172 never-smokers and 1376 ever-smokers with NSCLC underwent pulmonary resection. The 2 cohorts were matched on patient characteristics, histopathological cancer cell type, and pathological stage group using a weighted balancing score, and overall survival and cancer recurrence were compared by pathological stage. Random forests for survival was used to identify granular cancer characteristics with different survival and cancer recurrence importance between groups.

Results:

In never-smokers, the prevalence of NSCLC was more frequent in women than in men (63% [n = 109] vs 45% [n = 63]). Compared with ever-smokers, never-smokers had less upper-lobe disease (53% [n = 91] vs 62% [n = 855]) and more adenocarcinoma (88% [n = 151] vs 62% [n = 845]). Postoperative complications were similar. Never-smokers had a lower prevalence of non–lung cancer deaths than ever-smokers (13% vs 23% at 5 years; P = .006). Among matched pairs, never-smokers had better overall survival at 5 years in pathological stage I (96% vs 78%), but worse survival in stage II (54% vs 78%). Tumor size, N category, and histopathological cell type were more important drivers of mortality and cancer recurrence in never-smokers than in ever-smokers.

Conclusions:

NSCLC in never-smokers affects women more than men and presents with different anatomic and histopathological distributions. Matched never-smokers have better or equivalent outcomes than ever-smokers in pathological stage I cancer, but are less likely to survive and to be cured of cancer as tumor burden increases. These findings suggest that there might be unique tumor or host behaviors differentially impacting survival of never- and ever-smoking patients with NSCLC.

Graphical Abstract

Survival after resection for non–small cell lung cancer in never-smokers and ever-smokers.

The proportion of never-smokers with non–small cell lung cancer (NSCLC) is rising^1,2; moreover, NSCLC in never-smokers may represent a distinct clinical entity.¹ Findings from genetic and proteomic analyses of NSCLC in never-versus ever-smokers^3–6 suggest differences in epidermal growth factor receptor biomarkers,⁷ transcriptional patterns that appear stratified by tobacco use,⁸ and overall molecular profiles of the cancers.⁹

Despite sophisticated laboratory studies, clinical studies aimed at segregating NSCLC in never-smokers from that in ever-smokers have not been as informative. Cohort studies suggest that never-smokers survive longer, but this might be confounded by differing frequency of adenocarcinoma, female sex, race, performance status, comorbidities, and suboptimal clinical staging by positron emission tomography scanning in smokers.^10–16 One matched study identified no differences in survival for never- versus ever-smokers with NSCLC, but this study was limited by underrepresentation of early-stage disease,¹⁶ whereas another study suggests an important difference.¹⁷ Finally, confounding of survival estimates by non–lung cancer deaths remains incompletely understood.¹⁰

Therefore, we reviewed our experience with resected NSCLC from never- and ever-smokers to characterize differences in demographics and clinical presentation, periresection outcomes, mortality, and cancer recurrence. We used matching based on a balancing score to account for differences in comorbidities associated with tobacco use, thereby isolating NSCLC-related differences, and machine learning to identify survival and cancer recurrence differences related to individual cancer characteristics, unrestrained by coarse stage grouping.

METHODS

Patients

From January 2006 to July 2016, 1548 patients underwent pulmonary resection for NSCLC at Cleveland Clinic. These patients included 172 (11%) never-smokers and 1376 (89%) ever-smokers (Table 1). Smoking status was abstracted from patients’ self-reported social history in the medical record. The Cleveland Clinic Institutional Review Board approved use of these data for research (approval no. 13–411; August 22, 2017), with patient consent waived.

TABLE 1.

Patient characteristics of ever-smokers and never-smokers before and after matching (N = 1548)

	Before matching					After matching
Characteristic	Never-smokers (n = 172)		Ever-smokers (n = 1376)		Standardized difference, %	Never-smokers (n = 169)		Ever-smokers (n = 165)		Standardized difference, %
	n*	No. (%) or 15th/50th/85th percentiles	n*	No. (%) or 15th/50th/85th percentiles		n*	No. (%) or 15th/50th/85th percentiles	n*	No. (%) or 15th/50th/85th percentiles
Demographics
Age, y	172	53/68/78	1376	56/68/77	−7.9	169	53/69/78	165	53/68/79	−2.6
Female sex	172	109 (63)	1376	623 (45)	37	169	106 (63)	165	103 (63)	0.09
Body surface area, m2	172	1.6/1.9/2.2	1376	1.7/1.9/2.2	−28	169	1.6/1.9/2.2	165	1.6/1.9/2.2	−1.4
Body mass index, kg/m2	172	22/26/32	1372	22/27/33	−15	169	22/26/32	165	22/26/32	0.73
Race
Black	169	10 (5.9)	1323	134(10)	−16	166	9.7 (5.9)	160	18(11)	−19
White	169	142 (84)	1323	1169 (88)	−13	166	140 (85)	160	139(87)	−6.7
Other	172	10 (5.8)	1376	2(0.15)	34	169	8.5 (5.1)	165	1.0 (0.63)	27
Smoking
Pack-years	172		1376		—	169		165		—
≤10		172 (100)		100 (7.3)			169 (100)		22(13)
11–20		0(0)		157 (11)			0(0)		29 (17)
21–40		0(0)		437 (32)			0(0)		58 (35)
41–60		0(0)		346 (25)			0(0)		31 (19)
≥61		0(0)		336 (24)			0(0)		26(16)
Lung function
FEV1, % of predicted	159	73/92/110	1291	63/81/101	54	156	74/93/108	157	73/93/111	−1.1
Lung diffusion test, % of predicted	121	72/89/106	999	56/74/93	80	120	72/89/106	119	66/85/112	8.8
Comorbidities
Hypertension	166	88 (53)	1346	836 (62)	−18	163	87 (53)	160	87 (55)	−2.2
Steroids	166	8 (4.8)	1346	88 (6.5)	−7.4	163	8 (4.9)	160	10 (6.3)	−6.1
Coronary artery disease	166	22 (13)	1346	318 (24)	−27	163	22 (14)	160	22(14)	0.06
Peripheral arterial disease	166	9 (5.4)	1346	144(11)	−19	163	8.7 (5.4)	160	9.1 (5.7)	−1.4
Prior cardiothoracic surgery	166	28 (17)	1345	223 (17)	0.77	163	28 (17)	160	27 (17)	−0.46
Preoperative chemotherapy	166	29 (17)	1346	164 (12)	15	163	28 (17)	160	26 (16)	2.5
Preoperative radiation	166	26 (16)	1346	172(13)	8.3	163	26 (16)	160	26 (16)	−0.82
Pharmacologically treated diabetes	172	21 (12)	1376	252(18)	−17	168	21 (13)	165	21(13)	−1.6

FEV1, Forced expiratory volume in 1 second.

^*Patients with data available.

Cancer Staging

All cancers were pathologically staged according to the 8th edition of the American Joint Committee on Cancer’s AJCC Cancer Staging Manual¹⁸ (Table 2).

TABLE 2.

Clinical cancer characteristics of ever-smokers and never-smokers before and after matching

	Before matching					After matching
Characteristic	Never-smokers (n = 172)		Ever-smokers (n = 1376)		Standardized difference, %	Never-smokers (n = 169)		Ever-smokers (n = 165)		Standardized difference, %
	n*	No. (%)	n*	No. (%)		n*	No. (%)	n*	No. (%)
Tumor location	172		1376			168		165
Right upper		51 (30)		498 (36)	−14		50 (30)		58 (35)	−11
Right middle		5 (2.9)		71 (5.1)	−11		5 (3.0)		11 (6.4)	−16
Right lower		45 (26)		255 (19)	18		45 (27)		35 (21)	13
Left upper		40 (23)		357 (26)	−6.2		38 (23)		42 (26)	−6.3
Left lower		28 (16)		184 (13)	8.2		27 (16)		20 (12)	11
Right central		2 (1.2)		14 (1.0)	1.4		2 (1.2)		0.95 (0.57)	6.5
Left central		2 (1.2)		19 (1.4)	−1.9		2 (1.2)		0.73 (0.44)	8.3
Focality	170		1373		0.55	167		165		−4.0
Unifocal		156 (92)		1262 (92)			154 (92)		150 (91)
Multifocal		14 (8.2)		111 (8.1)			13 (7.9)		15 (9.0)
Histopathological type	172		1373			169		165
Adenocarcinoma		151 (88)		845 (62)	63		148 (88)		146 (89)	−3.0
Large cell		2 (1.2)		60 (4.4)	−20		2 (1.2)		4.5 (2.8)	−11
Not otherwise specified		0(0)		18 (1.3)	−16		0(0)		1.3 (0.76)	−12
Other		9 (5.2)		31 (2.3)	16		9 (5.1)		3.0 (1.8)	18
Squamous		10 (5.8)		419 (31)	−68		10 (6.0)		9.8 (6.0)	−0.15
Invasion and involved margins
Visceral pleural invasion	167	55 (33)	1360	386 (28)	−9.9	164	54 (33)	163	44 (27)	13
Lymphovascular invasion	128	54 (42)	1049	426 (41)	3.2	124	52 (42)	126	53 (42)	−0.75
Soft tissue margin involved	120	7 (5.8)	1040	35 (3.4)	12	118	7 (5.9)	123	4.0 (3.2)	13
Bronchial margin involved	158	6 (3.8)	1230	13(1.1)	18	155	5.8 (3.8)	151	0.69 (0.46)	23
Vascular margin involved	161	3 (1.9)	1222	15 (1.2)	5.0	158	3 (1.9)	150	0.75 (0.5)	13
Parenchymal margin involved	103	1 (0.97)	902	9 (1.0)	−0.27	101	1 (0.99)	108	0.57 (0.53)	5.3
Pathological T category	172		1376			169		165
1a		7 (4.1)		104 (7.6)	−15		7 (4.1)		12 (7.1)	−13
1b		45 (26)		379 (28)	−3.1		44 (26)		47 (28)	−4.6
1c		47 (27)		341 (25)	5.8		46 (27)		42 (26)	3.3
2a		35 (20)		212(15)	13		34 (20)		25 (15)	13
2b		13 (7.6)		116 (8.4)	−3.2		13 (7.7)		14 (8.6)	−3.4
3		13 (7.6)		129 (9.4)	−6.5		13 (7.5)		17 (10)	−9.0
4		12 (7.0)		95 (6.9)	0.29		12 (7.1)		8.3 (5.0)	8.7
Pathological N category	172		1376			169		165
0		116 (67)		1007 (73)	−13		113 (67)		116 (70)	−6.1
1		35 (20)		241 (18)	7.2		35 (21)		30 (18)	5.8
2		21 (12)		126 (9.2)	9.9		20 (12)		19(11)	1.95
3		0(0)		2 (0.15)	−5.4		0(0)		0.13 (0.08)	−3.99
Pathological M category	172	170 (99)	1376	1353 (98)	−4.3	169	167 (99)	165	163 (99)	−0.74
Pathological stage group	172		1376		11	169		165		7.3
IA1		4 (2.3)		95 (6.9)			4 (2.3)		11 (6.5)
IA2		40 (23)		317 (23)			39 (23)		36 (22)
IA3		29 (17)		255 (19)			28 (16)		28 (17)
IB		19(11)		133 (9.7)			19(11)		14 (8.8)
IIA		6 (3.5)		63 (4.6)			6 (3.6)		8.2 (5.0)
IIB		41 (24)		252(18)			41 (24)		36 (22)
IIIA		27 (16)		203 (15)			26 (16)		25 (15)
IIIB		4 (2.3)		34 (2.5)			4 (2.3)		3.8 (2.3)
IIIC		0(0)		1 (0.07)			0(0)		0.03 (0.02)
IV		2 (1.2)		23 (1.7)			2 (1.2)		2.1 (1.3)

^*Patients with data available.

Cancer Therapy

The majority of cancers were removed by lobectomy: 85% in never-smokers and 78% in ever-smokers (Table E1). A thoracoscopic approach was used for 84 (48%) never-smokers and 691 (50%) ever-smokers. For patients with locally advanced disease (cIIIA), concurrent chemotherapy (platinum doublet) and radiotherapy (45–60 Gy) were administered and completed 4 to 6 weeks before resection. Not all medical therapy was delivered at our center.

Endpoints

Primary endpoints were all-cause mortality from date of operation and cancer recurrence, death before NSCLC recurrence, which we assumed to represent non-NSCLC deaths, and death after cancer recurrence. Secondary endpoints were 30-day complications, as defined by the Society of Thoracic Surgeons National Database (https://www.sts.org/registries-research-center/sts-national-database). Cancer recurrence was confirmed by tissue diagnosis in many patients or by an overwhelming clinical diagnosis in others, particularly in those with systemic disease. For the latter patients, standard staging modalities included positron emission tomography scan, magnetic resonance imaging, or computed tomography scan of the brain.

Follow-up

Patients underwent clinical and radiographic surveillance at 6 months, then annually according to our institutional protocol. The date of recurrence was the date of the first radiographic evidence of cancer recurrence before tissue diagnosis. Fifty percent of survivors were followed for >3.2 years, 25% for >5.6 years, and 10% for >8 years.

Data Analysis

Analyses were performed using SAS version 9.4 (SAS Institute, Cary, NC) and R version 3.5.3 (R Foundation for Statistical Computing, Vienna, Austria). Continuous variables are summarized as mean ± standard deviation or equivalent 15th, 50th (median), and 85th percentiles if the distribution was skewed. Categorical data are summarized as frequencies and percentages. Uncertainty is expressed by 68% confidence limits equivalent to ±1 standard error. Standardized differences were calculated for comparisons of never- and ever-smokers.¹⁹

Overview of data analysis.

The primary data analyses focused on all-cause mortality and cancer recurrence. Two complementary analyses were performed for both outcomes. The first was a nonparametric Kaplan–Meier comparison of never- and ever-smokers whose clinical characteristics were statistically balanced using a weighted balancing score. The second was a machine learning investigation of differences in survival and cancer recurrence according to individual cancer characteristics, adjusted for clinical characteristics of the 2 cohorts of patients. Appendix E1 includes details of the statistical analyses that are described briefly in what follows.

Characterization of never- versus ever-smokers.

Multivariable logistic regression was performed to develop a parsimonious model of preoperative factors associated with being a never-smoker versus an ever-smoker. Variables considered in this analysis are listed in Appendix E2 and include demographics, lung function, histopathological cancer type and pathological stage group, and comorbidities.

Balancing score matching.

Unlike a treatment, smoking is a natural experiment and violates the exchangeability assumption of propensity scores that are thought to lead to causal inference.²⁰ However, similar to comparing outcomes for a treatment, patient and cancer characteristics must be balanced. Thus, as originally noted by Rosenbaum and Rubin,²⁰ a balancing score can be generated, similar to a propensity score. To accomplish this, we augmented the previously described parsimonious model with other variables marked in Appendix E2, to form a saturated model. We then applied the weighting analog of pair matching developed by Li and Greene for outcome comparisons.^21,22 The effective population size was 168.5 patients (rounded to 169) for the matched never-smokers and 165.1 (rounded to 165) for the ever-smokers. The quality of matching is depicted in Figure E1. Outcomes between propensity-weighted groups were compared using either a bootstrap resampling method²³ or weighted time-to-event analysis.²⁴ To correctly estimate variance of the treatment effect and take into account uncertainty in the estimated balancing score, the bootstrap method was used.²³

Unconstrained characterization of outcomes.

Machine learning was used to better understand survival and cancer recurrence differences according to pathological stage, using cancer characteristics unconstrained by classical TNM characterization and stage groupings. These characteristics included histopathological cell type, tumor size as a continuous variable, nodal status, tumor location, tumor laterality, and visceral pleural invasion, according to smoking status. Two random forests for survival (RF-S)²⁵ models were developed for each outcome using the entire NSCLC dataset, one for the entire never-smoker cohort and one for the entire ever-smoker cohort. From these, we ascertained for each cancer characteristic the risk-adjusted importance of each variable and how it differed for never-smokers and ever-smokers.

Cancer Recurrence and Death Before Recurrence

Cancer recurrence and short- and long-term survival were assessed nonparametrically using the Kaplan–Meier method, stratified by never-smokers versus ever-smokers in the overall cohort and by groups within matched patients. Differences were tested using Cox proportional hazard regression and a bootstrap methodology.

RESULTS

Prevalence of Pulmonary Resections for NSCLC in Never-Smokers

From 2006 to 2017, the proportion of never-smokers in the resected NSCLC cohort remained stable, between 10% and 12% annually (Figure E2).

Differences in Patient and Cancer Characteristics

Age was similar between never- and ever-smokers, but never-smokers were more often women (63% vs 45%), had higher forced expiratory volume in 1 second (FEV₁, expressed as percentage of expected; median, 92% vs 81%), higher lung diffusion (expressed as percentage of expected; median, 89% vs 74%), and fewer comorbidities (see Table 1). Never-smokers were also more likely to have undergone induction therapy (21% vs 15%).

The distribution of characteristics and principal histopathological cell type of NSCLC differed between never-smokers and ever-smokers (Table 2). Never-smokers more often had adenocarcinoma (88% vs 62%; P < .0001) and less often squamous cell cancer (5.8% vs 31%; P < .0001). They also had less upper-lobe disease (53% vs 62%; P = .02). However, pathological stage at resection was similar in the 2 groups (P = .5).

Perioperative Mortality and Morbidity (Weighted Matched Cohorts)

Among matched patients, perioperative in-hospital mortality was 0.59% (n = 1) for never-smokers and 0.62% (n = 1) for ever-smokers (Table E2). Postoperative complications were similar for matched never- and ever-smokers within 30 days (27% vs 28%), including atrial arrhythmias (8.8% vs 12%), chest tube air leak (3.6% vs 3.0%), pulmonary embolus (1.2% vs 0.48%), pneumonia (1.2% vs 2.4%), and prolonged intubation (0.59% vs 0.25%).

Unadjusted Reference Survival and Cancer Recurrence

All-cause mortality.

There were 381 deaths, 33 among never-smokers and 348 among ever-smokers. Survival among never-smokers at 1, 5, and 8 years was 93%, 77%, and 67%, respectively. For reference, among ever-smokers it was 93%, 69%, and 60%, respectively (Figure 1, A).

FIGURE 1.

Survival after resection of non–small cell lung cancer in never-smokers (blue line and squares) and ever-smokers (red line and circles). Each symbol represents a death, and vertical bars are asymmetric 68% confidence limits equivalent to ±1 standard error. Numbers below the horizontal axis are patients remaining at risk. A, Overall cohorts. B, Weighted matched cohorts.

Cancer recurrence.

In the overall never-smoker cohort, estimated freedom from NSCLC recurrence was 68% at 5 years and, for reference, 78% among ever-smokers (Figure 2, A).

FIGURE 2.

Cancer persistence or recurrence after resection of non–small cell lung cancer in never-smokers (blue line and squares) and ever-smokers (red line and circles). Format is as in Figure 1. A, Overall cohorts. B, Weighted matched cohorts

Death before cancer recurrence.

There were 227 non–NSCLC-related deaths, 12 among never-smokers and 215 among ever-smokers. At 5 years, death before recurrence among never-smokers was 13% and, for reference, 23% among ever-smokers (Figure 3, A).

FIGURE 3.

Death before and after cancer recurrence following resection of non–small cell lung cancer in never-smokers (blue line and squares) and ever-smokers (red line and circles). Format is as in Figure 1, except that the plots are inverted. A, Death before cancer recurrence in overall cohorts. B, Death after cancer recurrence in overall cohorts. C, Death before cancer recurrence in weighted matched cohorts. D, Death after cancer recurrence in weighted matched cohorts.

Death after cancer recurrence.

There were 154 deaths after cancer recurrence, 21 among never-smokers and 133 among ever-smokers. At 3 years, death after cancer recurrence among never-smokers was 48% and, for reference, 70% among ever-smokers (Figure 3, B).

Weighted Matched Outcomes

All-cause mortality.

Survival at 1, 5, and 8 years was 94%, 77%, and 67%, respectively, among matched never-smokers versus 93%, 74%, and 64%, respectively, among matched ever-smokers (P = .2) (Figure 1, B).

Survival by pathological stage.

Stage I.

In a subset of 90 matched pairs of patients in pathological stage I, 5-year survival was 96% in never-smokers versus 78% in ever-smokers (Figure 4, A). Stage I cancers in matched never-smokers compared with matched ever-smokers were less likely to be pT1a, and thus patients were less likely to have pathological stage IA1 and more likely to have cancer in the left lower lobe and less likely to have it in the right middle lobe (Table E3).

FIGURE 4.

Survival and cancer recurrence after resection of pathological stage I and stage II non–small cell lung cancer in never-smokers (blue line and squares) and ever- smokers (red line and circles). Format is as in Figure 1. A, Survival in matched stage I cohorts. B, Survival in matched stage II cohorts. C, Freedom from cancer recurrence in matched stage I cohorts. D, Freedom from cancer recurrence in matched stage II cohorts.

Stage II.

In a subset of matched pairs of pathological stage II patients, the relationship was inverted to that of pathological stage I patients, with never-smokers having a 5-year survival of 54% versus 78% among ever-smokers (Figure 4, B). Stage II cancers of matched never-smokers compared with matched ever-smokers were more likely to have positive lymph nodes and be pathological stage IIB rather than IIA (Table E4).

Differential importance of risk factors for mortality.

In an unconstrained analysis of detailed cancer and patient risk factors, 3 cancer variables played a more important role in predicting mortality among never-smokers than among ever-smokers: tumor size (as a continuous variable), pN stage, and histopathological type (Figure 5, A). The differential effect on survival of the variable with the greatest difference in importance—tumor size—became apparent after 5 cm (Figure E3, A).

FIGURE 5.

Mirrored histogram for never-smokers and ever-smokers of risk-adjusted normalized variable importance (VIMP) for survival and cancer recurrence, showing only cancer characteristics with 95% confidence intervals and median represented by a vertical bar. Presentation is in descending order of importance for the ever-smoker cohort. A, Survival. B, Cancer recurrence. VPI, Visceral pleural invasion.

Cancer recurrence.

At 5 years, estimated freedom from NSCLC recurrence for matched never-smokers versus ever-smokers was 68% versus 79% (P = .04) (Figure 2, B). Among matched patients, those with stage I NSCLC experienced similar cancer recurrence (Figure 4, C), but after 1–1/2 years, matched never-smokers with stage II NSCLC experienced more cancer recurrence than ever-smokers (Figure 4, D). Variables of importance for cancer recurrence mirrored those for mortality, with differential effects between never-smokers and ever-smokers even more pronounced (Figure 5, B, and Figure E3, B).

Death before cancer recurrence.

Among matched patients, 3-year mortality before NSCLC recurrence was 5% in never-smokers and 12% in ever-smokers (P = .05) (Figure 3, C).

Death after cancer recurrence.

Among matched patients, 3-year mortality after recurrence was 48% in never-smokers and 66% in ever-smokers (P = .3) (Figure 3, D).

DISCUSSION

Principal Findings

During the study period, the proportion of never-smokers among resected NSCLC patients remained stable at approximately 10%. Compared with ever-smokers, never-smokers were more often female and had more lower-lobe disease and adenocarcinoma (Figure 6). Perioperative outcomes after resection were similar in the 2 groups.

FIGURE 6.

Differences in non–small cell lung cancer (NSCLC) characteristics and outcomes in never-smokers versus ever-smokers. In both pathological stage I and stage II NSCLC, distribution of cancer differs, as does survival. Never-smokers with stage I cancer have better survival than ever-smokers, and never-smokers with stage II cancer have worse survival than ever-smokers. This may be partly related to the heterogeneity of cancer characteristics within pathological cancer stages, as well as to apparent differences in effect of risk factors for mortality and cancer recurrence, such as effect of tumor size and presence of positive lymph nodes in never-smokers versus ever-smokers.

However, ever-smokers were more likely than never-smokers to die from causes other than their cancer before cancer recurrence. In the subset of matched patients with similar comorbidities, pulmonary function, performance status, and histopathological cell type and pathological stage, survival was similar on average, but there were surprising differences between never-smokers and ever-smokers based on TNM-constrained and TNM-unconstrained variables. Never-smokers with stage I NSCLC had better survival than ever-smokers, whereas the inverse was true for stage II disease, with never-smokers having worse survival and more rapid cancer recurrence compared with ever-smokers. By unconstrained analysis, absolute tumor size incrementally and disproportionately affected survival and cancer recurrence in never-smokers compared with ever-smokers. Moreover, unique histopathological descriptors of the primary tumor also appeared to have had differential effects on survival and cancer recurrence between the 2 groups, and we have attempted to separate out the effects of these numerous differences in patient and cancer characteristics on survival and recurrence. Not surprisingly, we demonstrate heterogeneity within the current staging system and how this may affect generalized statements of prognosis and survival.

Study Design

The first aim of this study was to identify differences in cancer characteristics and comorbidities between never-smokers and ever-smokers receiving surgical management. The second aim was to discover survival and cancer recurrence differences between never-smokers and ever-smokers once differences in patient and cancer characteristics were balanced. Thus, we created a balancing score to mitigate confounding variables, such as demographics, comorbidities, pulmonary function, and cancer characteristic differences between the 2 groups. Finally, having observed differences in survival and cancer recurrence with respect to constrained stage groupings, we investigated cancer characteristics in an unconstrained manner to identify possible disproportionate effects on outcomes between never-smokers and ever-smokers.

NSCLC in Never-Smokers

NSCLC in never-smokers is the seventh leading cause of cancer death in the United States.^17,26 Although tobacco use has decreased in the general population, lung cancer among never-smokers has increased, possibly due to environmental exposure or other incompletely identified variables. Never-smokers comprise 10% to 15% of all newly diagnosed lung cancers, and in women, the prevalence is comparable to that of cervical cancer.²⁷ Despite this, public health efforts are lacking for lung cancer screening in never-smokers.

We were initially puzzled as to how and why early-stage disease seemed so treatable in never-smokers while locally advanced disease was so poorly affected. We were somewhat comforted by this paradox having been reported by others, although with less stringent matching.¹⁷ We had assumed that the patients from the never- and ever-smoking groups had been managed equivalently, independent of final pathological stage, and wanted to discount the possibility of stage migration. We considered the possibility of subtle differences and inadequacies in TNM staging of patients with stage II disease, whereby never-smokers might have had more T1–2N1 disease and less T2b-3N0 disease. Some of these differences were found.

We then attempted to uncouple unique tumor characteristics from cancer stage using machine learning to tease out at a more granular level the effect of cancer presentation on survival and cancer recurrence. Our findings corroborated the notion that never-smokers do less well with locally advanced disease compared with ever-smokers. Specifically, absolute size of the index cancer, independent of T classification of tumor size, was more highly predictive of mortality and cancer recurrence in never-smokers and, surprisingly, less so in ever-smokers.

Nevertheless, we still do not know why advanced cancers in never-smokers are more difficult to treat. Could these cancers be less responsive to chemotherapy? No doubt more granular genetic assessment might provide the answer. For example, epidermal growth factor receptor (EGFR) tyrosine kinase mutations and echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase (EML4-ALK) gene rearrangements are more common in never-smokers and have been implicated in resistance to platinum-based chemotherapy.^3,4 Because these 2 mutations have been identified, targeted therapies have become available: erlotinib, afatinib, gefitinib, and osimertinib for EGFR mutations; crizotinib, ceritinib, alectinib, and brigatinib for ALK gene rearrangements. In addition, the efficacy of immune checkpoint inhibitors such as pembrolizumab (PD-L1 inhibitor) in randomized controlled trials has differed based on the varying proportions of never-smokers enrolled.⁵ This is because never-smokers tend to have lower PD-L1 mutation loads, decreasing the likelihood that they will benefit from immune mediators.⁶

Limitations

Never-smokers were identified by self-report; thus, we depended on patients being truthful and remembering any smoking. Differences in objective measures of lung function at least partially support differentiating these 2 groups of never-smokers and ever-smokers. Nevertheless, it may be asked whether the differences observed in our study are reasonable or a statistical artifact. Indeed, might the cancer of those who have quit smoking also be different? There is no way to ethically design a large-scale randomized trial with decades-long follow-up to allay skepticism; likely, universal genetic testing of these cancers will be needed to produce the answers. However, genetic tests for these cancers were performed in only one-third of our patients, precluding incorporation of genetic findings as non-TNM variables in our analyses. Previously, it was our institutional practice to test for mutations after cancer recurrence; today, all tumors are tested for known activating mutations.

Our series of never-smokers with resected NSCLC is limited in size and does not represent all never-smokers with NSCLC, because we have captured only surgically treated patients who had earlier-stage disease. This could be why we see no increase in the proportion of cases.²⁷ Vagaries of the staging system may have led to subtle differences in TNM staging between the groups, some of which we have identified and some of which we have not. These differences would not be balanced (we purposely matched patients on histopathological cell type and pathological stage only) and may have conspired to subtly confound our study. It is also conceivable that matching algorithms become less accurate when differential outcomes with respect to cancer characteristics are present. The random forest analyses confirmed these concerns.

Much as we would have liked to include histopathological subtypes, pathological sectioning and reporting has been sufficiently heterogeneous to preclude including these variables. This was also true of grade of differentiation.

When clinically indicated, diagnosis of cancer recurrence was confirmed histologically; however, this was not the case in every patient described as having recurrent disease. The latter patients were thoroughly assessed clinically and by radiographic findings and deemed to have recurrent disease. This may have added subtle biases to cancer recurrence findings.

Never-smokers were more likely to receive induction therapy, reflecting our institutional bias in selecting patients with higher performance status for induction therapy. Finally, our institutional reports of survival among patients undergoing resection of stage I disease seem higher than those typically reported. We have previously noted and published this observation,²⁸ which we believe is attributable in part to stage purification based on careful and complete lymphadenectomy.

CONCLUSIONS

Thought to be a disease associated with smoking, NSCLC has a sizeable effect on the never-smoker population. Diagnosis may be delayed because of the relative rarity of the disease in this overall healthy population; however, is 10% to 15% that rare? The other reason for delayed diagnosis is that some ever-smokers, unlike never-smokers, are now offered screening, increasing the likelihood of identifying occult NSCLC. Moreover, in never-smokers, NSCLC survival and cancer recurrence are uniquely affected by cancer stage, local lymph node involvement, and size of the primary tumor compared with matched ever-smokers. Specifically, there is a heterogeneous effect of tumor size as a predictor of outcomes between never- and ever-smokers, with survival and cancer recurrence of never-smokers much more sensitive to subtle increases in size of the index tumor. Does this mean that smoking status should now be incorporated into future staging systems for NSCLC? One could imagine that as granularity and detail of cancer descriptors and patient variables progress, the bland (and somewhat arbitrary) TNM descriptors will become increasingly obsolete. New algorithms will have to be devised to more accurately predict optimal index treatment and refined indications for adjuvant therapy, with the goal of improving outcomes for a given patient as precision care evolves. It is clear that preexisting comorbidities, such as tobacco use, should be worked into future survival and prognostic algorithms.

PERSPECTIVE

Although never-smokers outlive their ever-smoking counterparts after resection of non–small cell lung cancer, in matched patients, never-smokers have better survival and equivalent cancer recurrence only for stage I disease, but worse outcomes for stage II disease. Surprisingly, advanced tumor size and increased lymph node burden have a greater adverse effect on outcomes in never-smokers compared with ever-smokers.

Abbreviation and Acronym

NSCLC

non–small cell lung cancer

APPENDIX

Appendix

APPENDIX E1. DETAILED STATISTICAL METHODS

Characterization of Never-Smokers Versus Ever-Smokers

Multivariable logistic regression was performed to identify preoperative factors associated with being a never-versus ever-smoker. Variables considered in this analysis are listed in Appendix E2 and include demographics, lung function, cancer details, and comorbidities. Variable selection was based on 1000 bootstrap resampled datasets and automated stepwise data entry, with a P value for retention of .05. Then the frequency of occurrence was tabulated for single factors and closely related clusters of factors.^E1 A parsimonious model was generated from variables appearing in 50% or more bootstrap models.^E2

Missing values for some variables were managed before data analysis by 5-fold multiple imputation using chained equations (MICE).^E3 One of the 5 imputed datasets was used for variable selection. Then, for each imputed complete dataset, we estimated regression coefficients and their variance–covariance matrix. Estimates from the 5 models were aggregated to yield final regression coefficient estimates, the variance–covariance matrix, and P values.

Balancing-Score Matching

Unlike a treatment, smoking is a natural experiment and violates the exchangeability assumption of propensity scores that are thought to lead to causal inference.^E4 However, similar to comparing outcomes for a treatment, patient and cancer characteristics must be balanced. Thus, as originally noted by Rosenbaum and Rubin,^E4 a balancing score can be generated, which for a binary variable is similar to a propensity score. Thus, we augmented the parsimonious model with other variables marked in Appendix E2, forming a saturated model (C-statistic = 0.75). From this, a balancing score was generated for each patient based on 20 variables (see Appendix E2). We then applied the weighting analog to pair matching developed by Li and colleagues for outcomes comparisons.^E5,E6 This weighted matching method achieves close to 1:1 matching (without using any caliper width), but uses every patient in the datasets fractionally. It is a variant of inverse treatment probability weighting, but avoids the analytical issues usually encountered when the propensity score is near the probability boundary of 0 or 1. The effective population size was 168.5 patients (rounded to 169) for the matched never-smokers and 165.1 (rounded to 165) for the ever-smokers. The quality of matching is depicted in Figure E1.

Unconstrained Characterization of Survival

To better understand survival differences according to pathological stage, machine learning was employed using cancer characteristics unconstrained by classical TNM characterization and stage groupings. These characteristics included histopathological type, tumor size as a continuous variable, nodal status, tumor location, tumor laterality, and visceral pleural invasion, according to smoking status. Initially, missing values for variables were imputed using an “on-the-fly” method.^E7 Then, 2 random forest for survival models^E8 were developed using the entire NSCLC data set, with all-cause mortality as the outcome: one for the entire never-smoker cohort and one for the entire ever-smoker cohort. Computations were implemented using randomForestSRC R software with default settings using 1500 trees.^E8 Each tree was analyzed using a bootstrap sample of the original data. On average, each sample contains approximately two-thirds of the patients, meaning that unselected patients were available to assess prediction error for that tree. To assess the predictive importance of each variable, only the data for those unselected patients were used. Values for each variable were randomly permuted, and prediction error before and after random permutation calculated in this manner and averaged over all trees, generating a variable importance metric and 95% confidence intervals.^E9,E10 From these, we ascertained for each cancer characteristic the risk-adjusted variable importance of each variable and how it differed for never-smokers and ever-smokers.

Cancer Recurrence and Death Before Recurrence

Cancer recurrence and short- and long-term survival were assessed nonparametrically by the Kaplan–Meier method, stratified by never- versus ever-smokers in the overall cohort and by groups within matched patients. Differences were tested by the log-rank statistic before applying the matching weight. Statistical significance of differences was tested using the log-rank test before applying the matching weight and a bootstrap methodology using Cox proportional hazard regression after applying the matching weight.

APPENDIX E2. VARIABLES CONSIDERED IN THE ANALYSES

Demographics

Female,* age (y),* race (black, white,* other), weight (kg), height (cm), weight/height ratio, body surface area (m²), body mass index (kg/m²)*

Lung Function

Forced expiratory volume in 1 second (% of predicted),* lung diffusion test (% of predicted)*

Cancer Details

Histopathological type (squamous,* adenocarcinoma*), pathological stage group (0, IA, IB, IIA, IIB, IIIA, IIIB, IV),* tumor size (cm), pathological N stage, tumor location, laterality, visceral pleural invasion, grade, unifocal (vs multifocal), invasion (vascular, lymph node, lymphovascular), margin (vascular, soft tissue, bronchial)

Comorbidities

Hypertension,* steroid use,* heart failure, prior cardiothoracic surgery,* coronary artery disease,* peripheral arterial disease,* diabetes mellitus,* pharmacologically treated diabetes,* insulin-treated diabetes, non–insulin-treated diabetes (including diet),* chronic obstructive pulmonary disease, renal disease, weight loss over past 3 months (kg), preoperative creatinine (mg/dL),* preoperative hemoglobin (g/dL), cerebrovascular disease

Cancer Therapy

Preoperative chemotherapy,* preoperative radiation*

Surgical Details

Open procedure, video-assisted thoracoscopic surgery, lobectomy

Interval

Interval: 1/1/2006 to index operation*

FIGURE E1.

Quality of matching of never- and ever-smoker patient pairs. A, Mirrored histogram of distribution of balancing scores for never-smokers (bars below zero line) and ever-smokers (bars above zero line). Shaded area represents matched patient pairs. B, Standardized differences of selected variables before and after matching. Vertical dashed lines at −10% and +10% indicate boundaries of desirable matching. Black triangles represent standardized differences before propensity score–based matching, with positive values indicating a variable is more common in the never-smoker group and negative values indicating variables more common in the ever-smoker group. Green squares represent characteristics after matching. FEV₁, Forced expiratory volume in 1 second; CT, cardiothoracic; CAD, coronary artery disease.

FIGURE E2.

Prevalence of never-smokers in the resected non–smallcell lung cancer (NSCLC) cohort by calendar year. (Left) Proportion of never-smokers in the population of resected NSCLCs. The solid line is a smoothing spline curve, and dots represent the percentage of never-smokers each year. (Right) Stacked histogram of frequency of ever-smokers (red) and never-smokers (blue). Note: Numbers for 2016 go to July 2016 (half-year).

FIGURE E3.

Risk-adjusted partial dependency plots of 1-year survival and cancer recurrence after lung resection for non–small cell lung cancer. Never-smokers are represented by blue lines; ever-smokers, by red lines. Parallel lines represent similar survival trajectories for never- and ever-smokers. Diverging or crossing lines represent differences in survival implications for never- and ever-smokers, such as for histopathological type, presence of metastatic disease, crossing lines for tumor size, vascular margin and invasion, and lymphovascular invasion. Histology: 1 = adenocarcinoma, 2 = squamous cell cancer; focality: 0 = unifocal, 1 = multifocal; laterality: 0 = right, 1 = left; location: 1 = right upper, 2 = right middle, 3 = right lower, 4 = left upper, 5 = left lower, 6 = right central, 7 = left central. A, Survival. B, Freedom from cancer recurrence. VPI, Visceral pleural invasion.

TABLE E1.

Surgical procedures in ever-smokers and never-smokers before and after matching

	Before matching			After matching
Procedure*	Never-smokers (n = 172) No. (%)	Ever-smokers (n = 1376) No. (%)	Standardized difference, %	Never-smokers (n = 169) No. (%)	Ever-smokers (n = 165) No. (%)	Standardized difference, %
Wedge resection	8 (4.7)	91 (6.6)	−8.5	7.5 (4.4)	9.4 (5.7)	−5.8
Thoracoscopic wedge resection	14(8.1)	152 (11)	−10	14 (8.3)	16 (9.6)	−4.7
Segmentectomy	5 (2.9)	50 (3.6)	−4.1	4.9 (2.9)	3.8 (2.3)	3.5
Thoracoscopic segmentectomy	6 (3.5)	28 (2.0)	8.9	6 (3.6)	3.3 (2.0)	9.6
Lobectomy	94 (55)	726 (53)	3.8	92 (54)	87 (53)	3.1
Thoracoscopic lobectomy	54 (31)	354 (26)	13	52 (31)	52 (31)	−0.61
Pneumonectomy	12 (7.0)	115 (8.4)	−5.2	12 (7.0)	9.4 (5.7)	5.6

^*Procedures are not mutually exclusive.

TABLE E2.

Perioperative outcomes in matched ever-smokers versus never-smokers

Outcome	Never-smokers (n = 169)		Ever-smokers (n = 165)		P value†
	n*	No. (%)	n*	No. (%)
Hospital death	169	1 (0.59)	165	1 (0.62)	>.9
Atrial arrhythmia	169	15 (8.8)	165	19 (12)	.3
Ventricular arrhythmia	169	1 (0.59)	165	0 (0)	—
Myocardial infarction	169	0 (0)	165	0.05 (0.03)	—
Deep vein thrombosis	169	4 (2.4)	165	1.3 (0.78)	.17
Pulmonary embolus	169	2 (1.2)	165	0.79 (0.48)	—
Atelectasis	169	1 (0.59)	165	1.7 (1.1)	.5
Pneumonia	169	2 (1.2)	165	4 (2.4)	.2
Pneumothorax	161	2 (1.2)	155	0.78 (0.50)	—
Ventilator>48 h	169	1 (0.59)	165	0.41 (0.25)	—
Reintubation	162	2 (1.2)	155	3 (2.0)	.5
Acute respiratory distress syndrome	169	0 (0)	165	0.79 (0.48)	—
Chest tube air leak	169	6 (3.6)	165	5 (3.0)	.7
Bronchopleural fistula	169	0 (0)	165	0.17 (0.10)	—
Empyema	169	0 (0)	165	0.35 (0.21)	—
Chylothorax surgery	143	0 (0)	139	0.01 (0)	—
Tracheostomy	169	3 (1.8)	165	3 (1.8)	>.9
Central nervous system event	169	1 (0.59)	165	0.37 (0.22)	—
Paresis or paralysis	169	0 (0)	165	1.3 (0.8)	—
Gastrointestinal ileus	169	1 (0.59)	165	0.69 (0.42)	.8
Other G.I. complication	169	4.5 (2.7)	165	1.6 (0.94)	.16
Return to ICU	161	3 (1.9)	156	7.1 (4.5)	.06
Sepsis	169	0 (0)	165	0.28 (0.17)	—
Renal failure	143	1 (0.70)	139	0.18 (0.13)	—
Urinary retention	150	2 (1.3)	146	1.9 (1.3)	>.9
Urinary tract infection	169	3 (1.8)	165	2.2 (1.3)	.7
Discharged with Foley catheter	150	2 (1.3)	146	0.45 (0.31)	—
Other infectious complications	161	0 (0)	155	0.89 (0.57)	—
Wound infection	143	1 (0.7)	139	0.06 (0.04)	—
Return to operating room	161	4.5 (2.8)	155	4.4 (2.8)	.9
Reoperation for bleeding	135	0 (0)	130	0.73 (0.56)	—
Any of above complications	169	45 (27)	165	45 (28)	.8
Postoperative LOS, d‡	169	3/4/6	165	3/4/7	.4

GI, Gastrointestinal; ICU, intensivecare unit; LOS, length of stay.

^*Patients with data available.

^†Outcomes with frequency too low for weighted estimation of P value.

^‡15th/50th/85th percentiles.

TABLE E3.

Characteristics of pathological stage I non–small cell lung cancer in never-smokers versus ever-smokers

	Before matching					After matching
Characteristic	Never-smokers (n = 92)		Ever-smokers (n = 800)		Standardized difference, %	Never-smokers (n = 90)		Ever-smokers (n = 90)		Standardized difference, %
	n*	No. (%)	n*	No. (%)		n*	No. (%)	n*	No. (%)
Tumor location	92		800			90		90
Right upper		31 (34)		302 (38)	−8.4		30 (34)		32 (36)	−3.4
Right middle		2 (2.2)		45 (5.6)	−18		2 (2.2)		6.5 (7.2)	−23
Right lower		25 (27)		156 (19)	18		25 (28)		22 (24)	7.7
Left upper		20 (22)		203 (26)	−8.6		18 (21)		22 (25)	−10
Left lower		14 (15)		94 (12)	10		14 (15)		7.9 (8.8)	20
Right central		0(0)		2 (0.25)	−7.1		0(0)		0.03 (0.03)	−2.5
Left central		0(0)		1 (0.13)	−5.0		0(0)		0.03 (0.03)	−2.5
Focality	91		798		6.6	89		90		−2.9
Unifocal		84 (92)		750 (94)			83 (93)		83 (92)
Multifocal		7 (7.7)		48 (6.0)			6.1 (6.9)		6.8 (7.6)
Histopathological type	92		797			90		90
Adenocarcinoma		85 (92)		534 (67)	66		83 (92)		82 (92)	2.7
Large cell		0(0)		33 (4.1)	−29		0(0)		2.4 (2.7)	−23
Not otherwise specified		0(0)		9(1.1)	−15		0(0)		0.78 (0.87)	−13
Other		4 (4.3)		15 (1.9)	14		3.9 (4.4)		0.65 (0.73)	23
Squamous		3 (3.3)		206 (26)	−68		3 (3.4)		3.7 (4.2)	−4.3
Invasion and involved margins
Visceral pleural invasion	90	16 (18)	796	168 (21)	−8.4	88	16 (18)	90	18 (20)	−5.4
Lymphovascular invasion	69	15 (22)	600	151 (25)	−8.1	67	14 (20)	70	17 (24)	−9.1
Soft tissue margin involved	75	2 (2.7)	643	14 (2.2)	3.2	73	2 (2.7)	71	2 (2.8)	−0.61
Bronchial margin involved	83	3 (3.6)	681	2 (0.29)	24	81	3 (3.7)	78	0.12 (0.15)	26
Vascular margin involved	86	1 (1.2)	678	1 (0.15)	13	84	1 (1.2)	78	0.02 (0.02)	15
Parenchymal margin involved	54	0(0)	540	5 (0.93)	−14	52	0(0)	60	0.26 (0.43)	−9.2
Pathological T category	92		800			90		90
1a		4 (4.4)		95 (12)	−28		4 (4.5)		11 (12)	−27
1b		40 (43)		317 (40)	7.8		39 (44)		36 (41)	6.5
1c		29 (32)		255 (32)	−0.76		28 (31)		28 (31)	−1.4
2a		19 (21)		133 (17)	10		19 (21)		14 (16)	13
Pathological N category	92		800			90		90
0		92 (100)		800 (100)	—		90 (100)		90 (100)	—
Pathological M category	92	92 (100)	800	800 (100)	—	90	90 (100)	90	90 (100)	—
Pathological stage group	92		800		17	90		90	19
IA1		4 (4.4)		95 (12)			4 (4.5)		11 (12)
IA2		40 (43)		317 (40)			39 (43)		36 (41)
IA3		29 (32)		255 (32)			28 (31)		28 (31)
IB		19 (21)		133 (17)			19 (21)		14 (16)

^*Patients with data available.

TABLE E4.

Characteristics of pathological stage II non–small cell lung cancer in never-smokers versus ever-smokers

	Before matching					After matching
Characteristic	Never-smokers (n = 47)		Ever-smokers (n = 315)		Standardized difference, %	Never-smokers (n = 47)		Ever-smokers (n = 44)		Standardized difference, %
	n*	No. (%)	n*	No. (%)		n*	No. (%)	n*	No. (%)
Tumor location	47		315			47		44
Right upper		14 (30)		103 (32)	−6.3		14 (30)		14 (31)	−3.4
Right middle		2 (4.3)		14 (4.4)	−0.92		2 (4.3)		2.9 (6.5)	−9.6
Right lower		10 (21)		45 (14)	18		10 (21)		7.5 (17)	11
Left upper		14 (30)		86 (27)	5.5		14 (30)		12 (27)	7.0
Left lower		5(11)		50 (16)	−15		4.8 (10)		7.7 (17)	−20
Right central		1 (2.1)		7 (2.2)	−0.64		1 (2.2)		0.23 (0.53)	14
Left central		1 (2.1)		13 (4.1)	−11		1 (2.2)		0.53 (1.2)	7.4
Focality	46		314		−28	46		44		−25
Unifocal		45 (98)		288 (92)			45 (98)		41 (92)
Multifocal		1 (2.2)		26 (8.3)			1 (2.2)		3.3 (7.5)
Histopathological type	47		315			47		44
Adenocarcinoma		37 (79)		158 (50)	62		37 (79)		37 (84)	−12
Large cell		1 (2.1)		15 (4.8)	−14		1 (2.2)		1.6 (3.7)	−9.2
Not otherwise specified		0(0)		3 (0.95)	−14		0(0)		0.11 (0.25)	−7.0
Other		4 (8.5)		9 (2.9)	24		3.7 (8.0)		1.2 (2.8)	23
Squamous		5(11)		130 (41)	−74		5(11)		4.2 (9.5)	4.1
Invasion and involved margins
Visceral pleural invasion	46	22 (48)	309	94 (30)	36	46	22 (48)	43	12 (28)	40
Lymphovascular invasion	36	22 (61)	249	135 (54)	14	36	22 (61)	35	21 (60)	1.2
Soft tissue margin involved	27	2 (7.4)	234	7 (3.0)	20	27	2 (7.5)	32	0.45 (1.4)	29
Bronchial margin involved	45	3 (6.7)	305	5 (1.6)	25	45	2.8 (6.3)	43	0.3 (0.69)	31
Vascular margin involved	44	1 (2.3)	302	8 (2.7)	−2.4	44	1 (2.3)	43	0.48 (1.1)	9.1
Parenchymal margin involved	29	0(0)	203	0(0)	—	29	0(0)	29	0(0)	—
Pathological T category	47		315			47		44
1a		1 (2.1)		6(1.9)	1.6		1 (2.2)		0.37 (0.84)	11
1b		4 (8.5)		31 (9.8)	−4.6		4 (8.6)		4.9 (11)	−8.1
1c		10 (21)		56 (18)	8.8		10 (21)		9.1 (21)	2.1
2a		11(23)		50 (16)	19		11 (24)		6.4 (15)	23
2b		11(23)		96 (30)	−16		11 (24)		12 (28)	−10
3		10 (21)		76 (24)	−6.8		9.6 (21)		11(25)	−9.9
Pathological N category	47		315			47		44
0		16 (34)		139 (44)	−21		16 (33)		19 (43)	−20
1		31 (66)		176 (56)	21		31 (67)		25 (57)	20
Pathological M category	47	47 (100)	315	315 (100)	—	90	90 (100)	90	90 (100)	—
Pathological stage group	47		315		20	47		44		16
IIA		6(13)		63 (20)			6(13)		8.2 (19)
IIB		41(87)		252 (80)			41 (87)		36 (81)

^*Patients with data available.