Predictors of Extra-Pulmonary Metastatic Disease in Patients with Recurrent Lung Cancer

doi:10.21203/rs.3.rs-268973/v1

Background: Lung cancer is one of the leading causes of cancer-related mortality worldwide. Its poor prognosis is associated with late detection and high recurrence rates. We aimed to determine if certain imaging characteristics of lung cancer recurrence were predictors of extra-pulmonary metastatic disease.

Methods: We conducted a retrospective study of all patients at our institution with lung cancer recurrence detected on post-treatment imaging between January 2014-October 2019. Research ethics board approval was obtained. Included patients underwent pre-treatment imaging, surgical resection, and post-treatment imaging. Imaging characteristics and pathological findings of the pulmonary lesions were analyzed. Univariate logistic regression was performed to assess for potential predictors of extra-pulmonary metastatic disease. The variables evaluated were age, gender, original and recurrent lesion size and imaging characteristics, recurrence location, presence of chest wall or mediastinal invasion, lymphadenopathy, and malignancy subtype.

Results: 76 patients were included (33 males; mean age 70.9, standard deviation [SD] 7.7). The primary lesions were adenocarcinoma (N=50), squamous cell carcinoma (N=21), and other (N=5). The mean time to recurrence was 24.3 months (SD=18.8) from date of surgical excision. The two significant predictors of extra-pulmonary metastatic disease were: having >1 recurrent lesion (odds ratio [OR], 8.1; p=0.004), and the presence of suspicious lymphadenopathy at the time of recurrence (OR, 14.1; p<0.001).

Conclusion: In lung cancer recurrence, the presence of >1 recurrent lesion and suspicious lymphadenopathy at the time of recurrence were significant predictors of extra-pulmonary metastatic disease. These findings may help guide the risk stratification and management of patients with recurrent lung cancer.

Internal Medicine

Recurrent lung cancer

metastatic disease

computed tomography (CT) imaging

Lung cancer is an aggressive malignancy that is one of the major causes of cancer-related deaths in the United States [1, 2]. It is the second most common cancer in men and women, after prostate and breast, respectively [3]. However, despite it being the second most common, it is still the leading cause of death in both men and women [3]. Its poor prognosis has been associated with late detection and high rates of recurrence [4]. Observational studies have demonstrated a risk of recurrence ranging between 6–10% in the first four years following resection, with a decline to 2% thereafter [4]. Additionally, they showed the risk of metachronous tumors to be 3–6%, which did not diminish with time [4].

Although these risks are well documented, guidelines for proper routine follow-up vary internationally [5]. Currently, patients are routinely undergoing radiologic imaging follow-up, including chest radiographs and computed tomography (CT), for which the protocol varies between different institutions. Some international guidelines suggest radiographic follow-up biannually for the first 2 years and annually thereafter [5]. However, since differences exist in recommended guidelines, it is clear that the most beneficial regime for routine follow-up is less clear [5–8]. These investigations expose the patient to radiation and are costly in terms of time, money, and resources [9]. We believe that having a better understanding of the risks of recurrence could potentially save money, time, and radiation exposure. We hope that examining pre- and post-treatment PET/CT imaging and pathological tissue diagnoses will unveil common factors that could predict the risk of recurrence of lung cancer and/or development of extra-pulmonary metastatic disease following treatment.

Previous researchers have outlined how differing morphological characteristics of different lung cancers can predict post-operative prognosis [10–15]. For example, Iwano et al. [10] demonstrated that patients with non-small cell lung cancer (NSCLC) with solid nodules had a significantly worse prognosis than those with subsolid nodules (those containing mixed solid and ground-glass opacity [GGO] characteristics). Whereas, Hattori et al. [11] demonstrated that a NSCLC tumor with a GGO component had a more favorable prognosis. Meanwhile, other researchers have examined peritumoral characteristics, such as lymphovascular invasion (LVI), and how its presence is associated with tumor recurrence in lung adenocarcinoma (most common histological type of NSCLC) [12]. Another study demonstrated that patients with higher preoperative ¹⁸F-fluorodeoxyglucose (FDG) standardized uptake values (SUV) on positron emission tomography (PET) had higher recurrence rates [13, 14]. All of these studies [10–14] examined only pre-treatment PET/CT imaging to assess for predictors of pulmonary recurrence. Whereas, Sung et al. [15] examined pre-treatment CT imaging to demonstrate that the presence of LVI was a significant predictor of extra-pulmonary metastatic disease. Otherwise, the literature examining pre-treatment PET/CT imaging to predict extra-pulmonary metastatic disease with lung cancer recurrence is scarce.

We aim to further investigate the role of pre- and post-treatment imaging, as well as other variables, such as age, pathologic tissue diagnosis, and appearance on PET/CT to attempt to predict the risk of lung cancer recurrence in patients imaged at our institution. Specifically, our objective is to examine pre-treatment PET/CT and post-treatment CT imaging to assess for predictors of lung cancer recurrence, as well as predictors of extra-pulmonary metastatic disease in patients with recurrent lung cancer.

We conducted a retrospective study of all patients at our institution with lung cancer recurrence detected on post-treatment surveillance imaging from January 1, 2014 to October 31, 2019. Research ethics board approval was obtained. Eligible patients underwent pre-treatment PET/CT imaging, surgical resection, and follow-up CT imaging. Inclusion criteria was defined as the following: patients over the age of 18, tissue diagnosis available following lung cancer resection, and evidence of local or metastatic disease recurrence on post-treatment imaging. Patients without tissue diagnosis or pre- and post-treatment imaging at our institution were excluded.

A control group of patients who underwent pre- and post-treatment imaging and surgical resection during the same study period, who were over the age of 18, and had tissue diagnosis available following lung cancer resection, but did not demonstrate lung cancer recurrence, were included. The minimum length of follow-up imaging to ensure adequate time for detecting recurrence was 24 months. This cut-off was chosen because the mean time to recurrence in the experimental group was 24 months (Table 3).

Data on pre-treatment PET/CT and post-treatment CT imaging characteristics of the pulmonary lesions, as well as pathological findings was collected for each patient. Data for the following variables was obtained: age, gender, size and imaging characteristics (solid, subsolid, GGO, or solid and cystic) of the original and recurrent lesion, location of recurrence (at the surgical margin or distant from the surgical bed but within the lung parenchyma), presence of chest wall or mediastinal invasion, presence of lymphadenopathy, and malignancy subtype (SCC, adenocarcinoma, neuroendocrine, and other). Routine CT chest studies as part of the routine post-treatment follow-up were analyzed for these CT imaging characteristics. CT exams for the abdomen/pelvis and brain were also analyzed, if available, to assess for extra-pulmonary disease. Lymphadenopathy was considered suspicious when the nodes measured ³1.0 cm or demonstrated avid SUV uptake on PET/CT. All CT studies were reported by the staff radiologists at our institution (2-20 years of radiology experience) and reports were retrospectively analyzed to populate the dataset.

Univariate logistic regression was performed (STATA version 11.2; Texas, United States) for two separate analyses: 1) for assessment of clinical and/or imaging predictors of lung cancer recurrence in patients undergoing imaging follow-up for treated lung cancer (for the recurrence and control groups) and 2) for assessment of clinical and/or imaging predictors of extra-pulmonary metastatic disease in patients with pulmonary recurrence of disease (recurrence group only). Corresponding odds ratios (OR) and p-values were calculated. Two-tailed t-tests (for patient age and size of lesion) and Fisher’s exact tests (for gender, lesion characteristics, mediastinal/chest wall invasion, presence of suspicious lymphadenopathy, and malignancy subtype) were performed to compare patient and lung cancer characteristics on pre-treatment CT imaging between the recurrence and control group, and corresponding p-values were calculated. A p-value of ≤0.05 was considered statistically significant.

A total of 108 patients were included in the study period, of which 76 had lung cancer recurrence, while 32 were followed for a minimum of 24 months with no recurrent disease. Clinical and pre-treatment imaging characteristics for both recurrence and control groups are listed in Table 1. The patient demographics are similar between groups, with 33 (43%) and 14 (44%) males (recurrence group and control group, respectively; p=0.559) and mean age of 70.9±7.7 and 68.4±8.3 years (recurrence group and control group, respectively; p=0.215). The initial pulmonary lesion size was also similar between the recurrence and control group, measuring 3.0±1.7 and 2.9±2.0 cm, respectively (p=0.851). The mean time to recurrence was 24.3±18.8 months. The present study allowed for acceptable follow-up within the control group, with mean time for follow-up of 54.6±25 months. Table 1 displays the distribution of the different lesion characteristics (solid, subsolid, GGO, or solid and cystic), the presence of mediastinal and chest wall invasion, the location of suspicious lymphadenopathy, and the distribution of malignancy subtypes (SCC, adenocarcinoma, neuroendocrine, and other). Information on the TNM (tumor, node, and metastasis) stage classification (8^th Edition) of the recurrence and control groups on pre-treatment PET/CT is provided in Table 2. Table 3 displays characteristics of the recurrent lesion, including: time to recurrence, average number and size of recurrent lesions, and location of recurrence (at the surgical bed, distant to surgical bed, or metastatic). Recurrence distant to the surgical bed refers to recurrence within the lung parenchyma, that is not at the surgical margin. The most common location for extra-pulmonary metastatic disease was in the bones (N=8).

Predictors of pulmonary recurrence in the recurrence and control group are listed in Table 4. Age, gender, malignancy type, lesion size, lesion characteristics, and the presence of suspicious lymphadenopathy on pre-treatment imaging were not statistically significant predictors of local lung cancer recurrence. Predictors of extra-pulmonary metastatic disease in the recurrence group are listed in Table 5.At the time of lung cancer recurrence, the presence of >1 recurrent pulmonary lesion (OR, 8.1; p=0.004), as well as the presence of suspicious lymphadenopathy (OR, 14.1; p<0.001) were statistically significant predictors of extra-pulmonary metastatic disease. Original lesion size, location, and characteristics, as well as chest wall and mediastinal wall invasion on post-treatment CT imaging were not significant predictors of extra-pulmonary metastatic disease.

The present study retrospectively examined patients at our institution with primary lung cancer, who underwent surgical resection, and had pre-treatment PET/CT and post-treatment CT imaging. Patient and imaging characteristics as well as pathological findings of the pulmonary lesions were analyzed to assess for predictors of lung cancer recurrence and extra-pulmonary metastatic disease. This study demonstrated that the two predictors of extra-pulmonary metastatic lung recurrence were: 1) the presence of > 1 recurrent pulmonary lesion and 2) the presence of suspicious lymphadenopathy, on post-treatment CT imaging. Furthermore, lesion size, imaging characteristics, recurrence location relative to surgical bed, or chest wall invasion were not significant predictors of extra-pulmonary metastatic lung cancer recurrence. The reason that the presence of chest wall invasion did not show an association with extra-pulmonary metastatic lung cancer recurrence in this study may have been due to the small number of patients with that characteristic in this cohort.

Many researchers have examined pre-treatment CT imaging to evaluate different factors that may predispose patients to lung cancer recurrence, including CT imaging characteristics and malignancy subtype, to name a couple. However, few researchers have examined post-treatment CT imaging to predict extra-pulmonary metastatic disease with lung cancer recurrence. The current study examined both pre- and post-treatment CT imaging and demonstrated that the presence of > 1 recurrent pulmonary lesion and suspicious lymphadenopathy in follow-up CT examinations can predict metastatic recurrence outside of the thoracic cavity. Therefore, in the presence of these two findings on follow-up chest CT, the clinician can predict the likelihood of metastatic recurrence without the additional expended costs (time, resources, money, and radiation) of additional imaging. This additional information may help clinicians and patients decide on whether or not they wish to undergo further treatment or investigations if the likelihood of extra-pulmonary metastatic disease is higher.

The present study also demonstrated that age, gender, malignancy type, lesion size, lesion CT imaging characteristics, and the presence of suspicious lymphadenopathy on pre-treatment PET/CT imaging were not significant predictors of lung cancer recurrence. Whereas, other researchers have shown a poorer prognosis with solid nodules when compared to subsolid nodules [10, 16], or a more favorable prognosis in nodules with GGO [11, 17]. In regard to predicting prognosis based on lesion size, research groups have found that this comparison should only occur in the pure solid component of nodules [16, 17], with larger size corresponding with worse prognosis [16, 18–22]. The current study was inclusive of all subtypes of NSCLC, whereas other research groups have looked at different subtypes individually [10, 12, 14, 18, 23]. The present study did not find a correlation between malignancy type and disease recurrence, whereas Takei et al. [23] found the poorest prognosis with large cell neuroendocrine carcinoma. Compared to the present study, this disparity may be due to the lack of patients in our experimental group with neuroendocrine histological subtype (Table 1). The reason that lymph node metastasis did not show an association with disease recurrence in this study may have been due to the small number of lymph node metastases in this cohort.

This study had multiple limitations. This was a retrospective, single-center study, and it may not be generalized to other population cohorts. The subject population was small (76 patients) compared to most research groups investigating lung cancer recurrence. The majority of histological diagnoses were adenocarcinoma and SCC (93% of the recurrence group), with few patients with neuroendocrine or other NSCLC tissue diagnoses. Lesion size was measured manually without using computer-aided diagnosis, which lends itself to measurement variabilities [24]. CT exams were read by a single reader and the reports were retrospectively analyzed to populate the dataset. The current study also only included patients who underwent surgical resection. This criterion was used because surgical resection allowed for pathologic correlation as well as to ensure full resection of the lesion. Therefore, the results of the current study would not adequately apply to patients undergoing only chemotherapy and radiotherapy.

The two predictors of extra-pulmonary metastatic lung recurrence were: 1) the presence > 1 recurrent pulmonary lesion and 2) the presence of suspicious lymphadenopathy, on post-treatment CT imaging. These findings may help guide clinicians in risk stratification and management of patients with recurrent lung cancer, including the length and frequency of imaging follow-up.

Funding: Not applicable

Conflicts of Interest: On behalf of all authors, the corresponding author states that there is no conflict of interest.

Ethics Approval: Research ethics board approval was obtained (see Appendix A).

Consent to Participate: Not applicable

Consent for Publication: Not applicable

Availability of Data and Material: Not applicable

Code Availability: Not applicable

Author’s Contributions:
- Dr. Tyler Grey: study design, ethics application, data extraction, data analysis, manuscript drafting, article submission, and final approval prior to publishing.

- Dr. Abdullah Alabousi: study design, ethics application, data extraction, data analysis, manuscript editing, article submission, and final approval prior to publishing.

- Dr. Mostafa Alabousi: data analysis, manuscript editing, and final approval prior to publishing.

- Dr. Ehsan Haider: study design, ethics application, manuscript editing, article submission, and final approval prior to publishing.

Siegel RL, Miller KD, Jemal A. Cancer statistics, 2016. CA Cancer J Clin [Internet]. American Cancer Society; 2016;66:7–30. Available from: https://doi.org/10.3322/caac.21332
Alberg AJ, Ford JG, Samet JM. Epidemiology of lung cancer: ACCP evidence-based clinical practice guidelines (2nd edition). Chest. United States; 2007;132:29S-55S.
Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin. United States; 2010;60:277–300.
Lou F, Huang J, Sima CS, Dycoco J, Rusch V, Bach PB. Patterns of recurrence and second primary lung cancer in early-stage lung cancer survivors followed with routine computed tomography surveillance. J Thorac Cardiovasc Surg [Internet]. The American Association for Thoracic Surgery; 2013;145:75–82. Available from: http://dx.doi.org/10.1016/j.jtcvs.2012.09.030
Chen Y-Y, Huang T-W, Chang H, Lee S-C. Optimal delivery of follow-up care following pulmonary lobectomy for lung cancer. Lung Cancer (Auckland, NZ). 2016;7:29–34.
Mitchell J, Benamore R, Gleeson F, Belcher E. Computed tomography follow-up identifies radically treatable new primaries after resection for lung cancer. Eur J Cardio-thoracic Surg. 2020;57:771–8.
Postmus PE, Kerr KM, Oudkerk M, Senan S, Waller DA, Vansteenkiste J, et al. Early and locally advanced non-small-cell lung cancer (NSCLC): ESMO Clinical Practice Guidelines for diagnosis, treatment and follow-up. Ann Oncol Off J Eur Soc Med Oncol. England; 2017;28:iv1–21.
Jaklitsch MT, Jacobson FL, Austin JHM, Field JK, Jett JR, Keshavjee S, et al. The American Association for Thoracic Surgery guidelines for lung cancer screening using low-dose computed tomography scans for lung cancer survivors and other high-risk groups. J Thorac Cardiovasc Surg [Internet]. The American Association for Thoracic Surgery; 2012;144:33–8. Available from: http://dx.doi.org/10.1016/j.jtcvs.2012.05.060
Virgo KS, Naunheim KS, McKirgan LW, Kissling ME, Lin JC, Johnson FE. Cost of patient follow-up after potentially curative lung cancer treatment. J Thorac Cardiovasc Surg [Internet]. 1996;112:356–63. Available from: http://www.sciencedirect.com/science/article/pii/S0022522396702623
Iwano S, Umakoshi H, Kamiya S, Yokoi K, Kawaguchi K, Fukui T, et al. Postoperative recurrence of clinical early-stage non-small cell lung cancers: A comparison between solid and subsolid nodules. Cancer Imaging. Cancer Imaging; 2019;19:1–7.
Hattori A, Matsunaga T, Takamochi K, Oh S, Suzuki K. Importance of Ground Glass Opacity Component in Clinical Stage IA Radiologic Invasive Lung Cancer. Ann Thorac Surg [Internet]. The Society of Thoracic Surgeons; 2017;104:313–20. Available from: http://dx.doi.org/10.1016/j.athoracsur.2017.01.076
Koo HJ, Xu H, Choi CM, Song JS, Kim HR, Lee JB, et al. Preoperative CT predicting recurrence of surgically resected adenocarcinoma of the lung. Med (United States). 2016;95:1–9.
Kim HR, Kim DJ, Lee WW, Jheon S, Sung SW. The significance of maximum standardized uptake values in patients with stage I pulmonary adenocarcinoma. Eur J Cardio-thoracic Surg. 2009;35:712–7.
Lee HY, Lee SW, Lee KS, Jeong JY, Choi JY, Kwon OJ, et al. Role of CT and PET Imaging in Predicting Tumor Recurrence and Survival in Patients with Lung Adenocarcinoma: A Comparison with the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society Classification. J Thorac Oncol [Internet]. International Association for the Study of Lung Cancer; 2015;10:1785–94. Available from: http://dx.doi.org/10.1097/JTO.0000000000000689
Sung SY, Kwak Y-K, Lee S-W, Jo IY, Park JK, Kim KS, et al. Lymphovascular Invasion Increases the Risk of Nodal and Distant Recurrence in Node-Negative Stage I-IIA Non-Small-Cell Lung Cancer. Oncology. Switzerland; 2018;95:156–62.
Kamiya S, Iwano S, Umakoshi H, Ito R, Shimamoto H, Nakamura S, et al. Computer-aided Volumetry of Part-Solid Lung Cancers by Using CT: Solid Component Size Predicts Prognosis. Radiology. United States; 2018;287:1030–40.
Hattori A, Matsunaga T, Takamochi K, Oh S, Suzuki K. Neither Maximum Tumor Size nor Solid Component Size Is Prognostic in Part-Solid Lung Cancer: Impact of Tumor Size Should Be Applied Exclusively to Solid Lung Cancer. Ann Thorac Surg. Netherlands; 2016;102:407–15.
Tsutani Y, Miyata Y, Yamanaka T, Nakayama H, Okumura S, Adachi S, et al. Solid tumors versus mixed tumors with a ground-glass opacity component in patients with clinical stage IA lung adenocarcinoma: prognostic comparison using high-resolution computed tomography findings. J Thorac Cardiovasc Surg. United States; 2013;146:17–23.
Maeyashiki T, Suzuki K, Hattori A, Matsunaga T, Takamochi K, Oh S. The size of consolidation on thin-section computed tomography is a better predictor of survival than the maximum tumour dimension in resectable lung cancer. Eur J Cardio-thoracic Surg. 2013;43:915–8.
Roviaro G, Varoli F, Vergani C, Nucca O, Maciocco M, Grignani F. Long-term survival after videothoracoscopic lobectomy for stage I lung cancer. Chest. United States; 2004;126:725–32.
Nakamura S, Fukui T, Taniguchi T, Usami N, Kawaguchi K, Ishiguro F, et al. Prognostic impact of tumor size eliminating the ground glass opacity component: modified clinical T descriptors of the tumor, node, metastasis classification of lung cancer. J Thorac Oncol. United States; 2013;8:1551–7.
Uehara H, Tsutani Y, Okumura S, Nakayama H, Adachi S, Yoshimura M, et al. Prognostic role of positron emission tomography and high-resolution computed tomography in clinical stage IA lung adenocarcinoma. Ann Thorac Surg [Internet]. Elsevier Inc; 2013;96:1958–65. Available from: http://dx.doi.org/10.1016/j.athoracsur.2013.06.086
Takei H, Asamura H, Maeshima A, Suzuki K, Kondo H, Niki T, et al. Large cell neuroendocrine carcinoma of the lung: a clinicopathologic study of eighty-seven cases. J Thorac Cardiovasc Surg. United States; 2002;124:285–92.
Iwano S, Okada T, Koike W, Matsuo K, Toya R, Yamazaki M, et al. Semi-automatic volumetric measurement of lung cancer using multi-detector CT effects of nodule characteristics. Acad Radiol. United States; 2009;16:1179–86.

Table 1: Patient and Lung Cancer Characteristics.

PATIENT CHARACTERISTICS	Recurrence Group	Control Group	p-value
Number of Subjects	76	32	-
Male (%)	33 (43)	14 (44)	0.559
Female (%)	43 (57)	18 (56)	0.559
Age (years±SD)	70.9±7.7	68.4±8.3	0.215
ORIGINAL LESION
Size (cm±SD)	3.0±1.7	2.9±2.0	0.851
Characteristics
Solid (%)	59 (78)	19 (59)	0.322
Subsolid (%)	9 (12)	5 (16)
GGO (%)	2 (3)	2 (6)
Solid and Cystic (%)	6 (8)	6 (19)
Invasion
Mediastinal Invasion	0	1	0.345
Chest Wall Invasion	2	0	0.544
Suspicious Lymphadenopathy
Ipsilateral Hilar (% of all patients)	8 (11)	2 (6)	0.744
Mediastinal (% of all patients)	11 (14)	3 (9)
Contralateral Hilar (% of all patients)	1 (1)	0 (0)
Supraclavicular (% of all patients)	5 (7)	0 (0)
Total (% of all patients)	25 (33)	5 (16)
Malignancy
SCC (%)	21 (28)	7 (22)	0.100
Adenocarcinoma (%)	50 (66)	23 (72)
Neuroendocrine (%)	0 (0)	2 (6)
Other (%)	5 (7)	0 (0)
Values are expressed as number ± standard deviation (SD); GGO, ground-glass opacity; SCC, squamous cell carcinoma

Table 2. TNM Classification (8^th Edition) for the Recurrence and Control Groups from Pre-Treatment PET/CT Imaging.

T Stage	Recurrence Group	Control Group	N Stage	Recurrence Group	Control Group	M Stage	Recurrence Group	Control Group
1a	5	1	0	59	29	0	75	32
1b	17	13	1	8	0	1a	1	0
1c	21	6	2	5	3	1b	0	0
2a	10	5	3	4	0	1c	0	0
2b	3	2
3	13	1
4	7	4
Total:	76	32		76	32		76	32
T (tumor); N (node); M (metastasis).

Table 3: Lung Cancer Characteristics of the Recurrent Lesions.

LESION CHARACTERISTICS	Recurrence Group
Time to Recurrence (months±SD)	24.3±18.8
Average Number of Recurrent Lesions (N±SD)	2.2±2.4
Average Size of Recurrent Lesions (cm±SD)	1.7±1.3
Location
Recurrence at the Surgical Bed (%)	23 (30)
Recurrence Distant to the Surgical Bed (%)	53 (70)
Metastatic Recurrence (%)	13 (17)
Values are expressed as number ± standard deviation (SD); Recurrence distant to the surgical bed refers to recurrence within the lung parenchyma, that is not at the surgical bed.

Table 4: Predictors of Pulmonary Recurrence on Pre-Treatment Imaging in the Recurrence and Control Groups.

	Recurrence Group			Control Group
Variable	Odds Ratio (95% CI)	Standard Error	p-value	Odds Ratio (95% CI)	Standard Error	p-value
Age	1.06 (0.97-1.15)	0.05	0.20	1.05 (0.99-1.10)	0.03	0.11
Gender (female; reference: male)	0.47 (0.13-1.65)	0.30	0.24	1.05 (0.45-2.41)	0.45	0.92
ORIGINAL LESION
Type (Adenocarcinoma; reference: SCC)	1.00 (0.23-4.31)	0.75	1.00	0.71 (0.26-1.91)	0.36	0.50
Type (Other; reference: SCC)	4.00 (0.46-34.92)	4.42	0.21	0.833 (0.13-5.30)	0.79	0.85
Size of Original Lesion	0.93 (0.63-1.35)	0.18	0.69	1.04 (0.82-1.32)	0.13	0.72
Size of Original Lesion at 3cm cut-off (>3cm; reference: <3cm)	1.33 (0.38-4.69)	0.86	0.66	1.07 (0.45-2.56)	0.48	0.87
Characteristics of Original Lesion (solid & cystic/GGO; reference: solid)	0.27 (0.03-2.23)	0.29	0.22	0.43 (0.18-1.04)	0.19	0.06
Lymphadenopathy on PET/CT (yes; reference: no)	1.65 (0.47-5.88)	1.07	0.44	2.54 (0.87-7.41)	1.39	0.09
CI, confidence interval; SCC, squamous cell carcinoma; GGO, ground-glass opacity

Table 5: Predictors of Extra-Pulmonary Metastatic Disease on Post-Treatment Imaging in the Recurrence Group.

*Variable*	*Odds Ratio* *(95% CI)*	*Standard Error*	*p-value*
Recurrent Lesions* (>1; reference: 1)	8.11 (1.96-33.59)	5.88	0.004
Size of Dominant Recurrent Lesion	1.30 (0.86-1.98)	0.28	0.22
Size of Dominant Recurrent Lesion - 3cm cut-off (>3cm; reference =<3cm)	2.29 (0.51-10.30)	1.76	0.28
Location (distant from surgical bed; reference: at surgical margin)	0.52 (0.15-1.85)	0.34	0.31
Characteristics of Recurrent Lesion (solid & cystic/GGO; reference: solid)	0.18 (0.02-1.50)	0.20	0.11
Chest or Mediastinal Wall Invasion (yes; reference: no)	1.34 (0.14-13.16)	1.56	0.80
Lymphadenopathy on CT* (yes; reference: no)	14.18 (3.30-61.04)	10.56	<0.001
CI, confidence interval; GGO, ground-glass opacity; *, significant difference (p≦0.05).

APPENDIXA.docx

Predictors of Extra-Pulmonary Metastatic Disease in Patients with Recurrent Lung Cancer

Status:

Version 1

Abstract

Introduction

Methods

Results

Discussion

Conclusion

Declarations

References

Tables

Supplementary Files

Status:

Version 1