Multidisciplinary management improves survival at 1 year after surgical treatment for non-small-cell lung cancer: a propensity score-matched study

Multidisciplinary management improves survival at 1 year after surgical treatment for... Abstract OBJECTIVES The management of patients affected by lung cancer requires the expertise of specialists from different disciplines. Although the advantages of multidisciplinary team discussions seem obvious, there are limited studies evaluating the influence of this approach on postoperative outcomes in non-small-cell lung cancer (NSCLC). The aim of this study is to examine the impact of a multidisciplinary approach on survival of patients undergoing surgery for NSCLC. METHODS A retrospective analysis was performed on consecutive patients who underwent surgery for NSCLC between January 2008 and December 2015. Data were compared between patients treated before the implementation of a multidisciplinary tumour board (MTB), between 2008 and 2012, and those who received treatment after the implementation of the MTB, between 2012 and 2015. Patients were matched one to one according to the discussion of the MTB and on the basis of a propensity score built using several patient characteristics. A propensity score-matched analysis was performed to compare patient outcomes. RESULTS A total of 246 patients were treated prior to the initiation of the MTB and 231 patients after the initiation of the MTB. Based on the propensity score, 2 well-matched groups of 170 patients were identified. Patients who were discussed at the MTB were noted to have better outcomes when compared with those who were not discussed at the MTB on different terms including complete staging evaluation, early tumour, node and metastasis (TNM) stages and 1-year survival rate. CONCLUSIONS Implementation of a multidisciplinary thoracic malignancy conference increased the 1-year survival rate of patients who underwent a surgical resection for NSCLC. Multidisciplinary approach, Quality of care, Surgical treatment, Multidisciplinary thoracic tumour board, Non-small-cell lung cancer, Patient outcome INTRODUCTION A multidisciplinary tumour board (MTB) brings together all teams involved in a patient’s care, including physicians (oncologists, radiologists, anaesthetists, surgeons, pulmonologists and pathologists), nurses, social workers, dieticians, physiotherapists and occupational therapists. The MTB members share their expertise, professional perspective and knowledge, and conferences are designed to enhance patient management and outcomes. Despite the absence of randomized trials, indirect evidence has shown a measureable improvement in outcomes since the introduction of multidisciplinary cancer care. However, the ability to measure the true effect of multidisciplinary care on cancer survival is limited by the inability to disentangle the effects of socioeconomic status, health service deprivation and heterogeneity of tumour stage from those secondary to implementation of a multidisciplinary approach and inherent improvements in cancer treatments over time. Although some data are available suggesting that managing lung cancer patients within an MTB results in timely access to treatment and adherence to guidelines, to date, specific evidence is not available regarding the impact of this model of lung cancer care on survival or patient satisfaction [1]. The aim of this study is to evaluate the impact of lung cancer MTB on different outcomes including 1-year survival by comparing patients treated before and after the establishment of a prospective, multidisciplinary care conference. METHODS Study design and population This study was conducted at the Ferrara University Hospital, which is a tertiary centre for thoracic surgery. A multidisciplinary thoracic tumour board responsible for the management of patients with known or suspected lung, pleural or mediastinal malignancies was established in 2012. The MTB meeting is held weekly and attendees include surgeons, pulmonary oncologists, radiation oncologists, radiologists, nuclear medicine specialists, pulmonologists, pathologists, lung cancer care coordinators and trainees. A management strategy is formulated and documented for each patient at the MTB meeting. An MTB database is created to assist with patient management. The data collected include patient demographics, smoking and occupational exposures, clinical parameters, patient performance status and comorbidities, tumour characteristics, treatment methods and survival. This retrospective cohort analysis is performed with the permission of the institutional ethics board. All consecutive patients who underwent surgery with curative intent for non-small-cell lung cancer (NSCLC) at our department between January 2008 and December 2015 were identified using the MTB and institution’s database. A retrospective analysis of these patient records was performed. Demographic data, completeness of staging, multidisciplinary evaluation prior to the initiation of therapy, preoperative diagnosis, pathological stages, surgical procedure, completeness of resection, hospital stay, postoperative complications and 1-year survival were all assessed. Overall survival was calculated from the day of surgery. Performance status was classified according to the Eastern Co-operative Oncology Group (ECOG) score [2] and comorbidities and postoperative complications were defined according to the Charlson Comorbidity Index Score [3] and the Ottawa thoracic morbidity and mortality classification system score [4], respectively. During the period under evaluation, the seventh edition of the tumour, node and metastasis (TNM) staging system replaced the sixth edition. Therefore, for this analysis, all patients were restaged using the seventh edition of the TNM staging system [5] based on information from bronchoscopy/endobronchial ultrasound/oesophageal ultrasound, computed tomography scan, fluorodeoxyglucose-positron emission tomography scan and a magnetic resonance imaging or computed tomography of the brain and the final pathology report. Two study groups were identified based on whether patients had their care prospectively coordinated through the institution’s multidisciplinary thoracic malignancy care conference or were treated prior to the conference’s implementation. Exclusion criteria included patient refusal of treatment following diagnosis, patients with superior sulcus tumours, patients undergoing surgery for NSCLC metastasis according to the Martini and Metamed criteria [6] and patients undergoing surgery with diagnostic or palliative intent. Complete preoperative evaluation The minimum preoperative evaluation was defined as a minimum of computed tomography scan, including the chest, upper abdomen and adrenal glands, positron emission tomography, bronchoscopy, complete blood count, electrolyte profile, pulmonary function tests and further evaluation of any specific symptoms. Statistical analysis Propensity score matching was performed to create 2 groups with no difference with respect to confounding factors. Propensity score was estimated using the logistic regression model with discussion of the MTB as the outcome. The following explanatory variables were included in the analysis: age, sex, the ECOG score >0, the Charlson Comorbidity Index, neoadjuvant therapy and pneumonectomy (Table 1). Patients were matched using the ‘nearest neighbour’ procedure with a maximum difference in propensity score of 10% of its standard deviation. Table 1: Clinical characteristics of the 2 cohorts of lung cancer patients identified for propensity score matching Variables Patients P-value Not discussed by MTB (n = 246) Discussed by MTB (n = 186) Gender, n (%) 189 (77) 128 (69) 0.05 Age (years), mean ± SD 69.9 ± 8.3 68.1 ± 8.2 0.02 Smoke, n (%) 0.53  Current 72 (30) 49 (26)  Previous 159 (65) 121 (65) Pack-years, median (IQR) 35 (20–50) 40 (20–52) 0.29 Alcoholism, n (%) 13 (5) 7 (4) 0.31 ECOG score >0, n (%) 24 (10) 14 (7) 0.42 COPD, n (%) 53 (21) 38 (20) 0.78 Charlson, mean ± SD 4.8 ± 1.6 4.7 ± 1.7 0.47 Neoadjuvant therapy, n (%) 19 (8) 12 (6) 0.61 Histology, n (%) 0.84  Adenocarcinoma 151 (61) 119 (64)  Squamous cell carcinoma 81 (33) 58 (31) Adjuvant therapy, n (%) 50 (20) 25 (13) 0.29 VATS, n (%) 22 (9) 89 (48) 0.001 Variables Patients P-value Not discussed by MTB (n = 246) Discussed by MTB (n = 186) Gender, n (%) 189 (77) 128 (69) 0.05 Age (years), mean ± SD 69.9 ± 8.3 68.1 ± 8.2 0.02 Smoke, n (%) 0.53  Current 72 (30) 49 (26)  Previous 159 (65) 121 (65) Pack-years, median (IQR) 35 (20–50) 40 (20–52) 0.29 Alcoholism, n (%) 13 (5) 7 (4) 0.31 ECOG score >0, n (%) 24 (10) 14 (7) 0.42 COPD, n (%) 53 (21) 38 (20) 0.78 Charlson, mean ± SD 4.8 ± 1.6 4.7 ± 1.7 0.47 Neoadjuvant therapy, n (%) 19 (8) 12 (6) 0.61 Histology, n (%) 0.84  Adenocarcinoma 151 (61) 119 (64)  Squamous cell carcinoma 81 (33) 58 (31) Adjuvant therapy, n (%) 50 (20) 25 (13) 0.29 VATS, n (%) 22 (9) 89 (48) 0.001 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; MTB: multidisciplinary tumour board; SD: standard deviation; VATS: video-assisted thoracoscopic surgery. Table 1: Clinical characteristics of the 2 cohorts of lung cancer patients identified for propensity score matching Variables Patients P-value Not discussed by MTB (n = 246) Discussed by MTB (n = 186) Gender, n (%) 189 (77) 128 (69) 0.05 Age (years), mean ± SD 69.9 ± 8.3 68.1 ± 8.2 0.02 Smoke, n (%) 0.53  Current 72 (30) 49 (26)  Previous 159 (65) 121 (65) Pack-years, median (IQR) 35 (20–50) 40 (20–52) 0.29 Alcoholism, n (%) 13 (5) 7 (4) 0.31 ECOG score >0, n (%) 24 (10) 14 (7) 0.42 COPD, n (%) 53 (21) 38 (20) 0.78 Charlson, mean ± SD 4.8 ± 1.6 4.7 ± 1.7 0.47 Neoadjuvant therapy, n (%) 19 (8) 12 (6) 0.61 Histology, n (%) 0.84  Adenocarcinoma 151 (61) 119 (64)  Squamous cell carcinoma 81 (33) 58 (31) Adjuvant therapy, n (%) 50 (20) 25 (13) 0.29 VATS, n (%) 22 (9) 89 (48) 0.001 Variables Patients P-value Not discussed by MTB (n = 246) Discussed by MTB (n = 186) Gender, n (%) 189 (77) 128 (69) 0.05 Age (years), mean ± SD 69.9 ± 8.3 68.1 ± 8.2 0.02 Smoke, n (%) 0.53  Current 72 (30) 49 (26)  Previous 159 (65) 121 (65) Pack-years, median (IQR) 35 (20–50) 40 (20–52) 0.29 Alcoholism, n (%) 13 (5) 7 (4) 0.31 ECOG score >0, n (%) 24 (10) 14 (7) 0.42 COPD, n (%) 53 (21) 38 (20) 0.78 Charlson, mean ± SD 4.8 ± 1.6 4.7 ± 1.7 0.47 Neoadjuvant therapy, n (%) 19 (8) 12 (6) 0.61 Histology, n (%) 0.84  Adenocarcinoma 151 (61) 119 (64)  Squamous cell carcinoma 81 (33) 58 (31) Adjuvant therapy, n (%) 50 (20) 25 (13) 0.29 VATS, n (%) 22 (9) 89 (48) 0.001 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; MTB: multidisciplinary tumour board; SD: standard deviation; VATS: video-assisted thoracoscopic surgery. Continuous data were expressed as means ± standard deviation or as median and interquartile range (IQR), whereas categorical variables were summarized as absolute frequencies and percentages. After propensity score matching was performed, differences between the 2 groups (MTB no/yes and alive/deceased after 1 year) were assessed using the χ2 test or the Fisher’s exact test for categorical variables and the Student’s t-test or the non-parametric Mann–Whitney U-test for continuous data, as appropriate. To evaluate the significance of the MTB discussion as a factor for the outcome of 1-year mortality after surgical treatment, a simple Cox regression model was carried out. To measure the net effect of the MTB, the model was then adjusted adding on the variables that were significantly associated with death. Finally, unnecessary variables were removed using a stepwise backward selection technique (P-value for removal = 0.1), and a more parsimonious multiple model was obtained; hazard ratios and their 95% confidence interval were reported. Results were considered statistically significant at P < 0.05. All analyses were performed using R version 3.4.0 (R Core Team (2017)) and Stata 13.0 for Windows (StataCorp, College Station, TX, USA). RESULTS Patient and treatment characteristics In total, 488 consecutive patients with NSCLC were treated and included in this study. Eleven patients were excluded because of lack of patients’ charts. In the remaining 477 patients, 246 were treated before the MTB implementation and 231 patients underwent surgery after the MTB discussion, 45 of whom were treated after 2012 without the MTB evaluation and were, therefore, excluded from our analysis. During the study period, an increased proportion of cases undergoing surgery for lung cancer was presented at the MTB meeting (Fig. 1): in 2015, 92% of cases were presented during the MTB meeting, whereas in 2012, only 46% of cases were discussed. Figure 1: View largeDownload slide Proportion of patients presented at MTB meetings (blue) before surgery between 2012 and 2015. MTB: multidisciplinary tumour board. Figure 1: View largeDownload slide Proportion of patients presented at MTB meetings (blue) before surgery between 2012 and 2015. MTB: multidisciplinary tumour board. Demographic data for the 2 groups are summarized in Table 1. In the MTB discussion group, a lower proportion of men and mean age can be noted. Furthermore, significantly more patients in the MTB group underwent lung resection by video-assisted thoracoscopic surgery when compared with the non-MTB group (48% vs 9%). All the other variables were comparable between the 2 groups. Specifically, the distribution of tumour histology, smoking history and chronic obstructive pulmonary disease did not differ significantly between the 2 groups. The mean Charlson Comorbidity Index was 4.7, and a similar proportion of patients undergoing neoadjuvant and adjuvant treatments was observed in both groups. Two homogeneous groups of 170 patients each (the no MTB discussion and MTB discussion groups) were identified based on the propensity score including 6 different variables. The demographic, clinical and histological characteristics of both groups are summarized in Table 2. Table 2: Clinical data based on the propensity scores Variables Patients P-value Not discussed by MTB (n = 170) Discussed by MTB (n = 170) Gender, n (%)  Male 124 (73) 124 (73) 1.00  Female 46 (27) 46 (27) Age (years), mean ± SD 68.8 ± 8.4 68.9 ± 7.9 0.95 Smoke, n (%) 0.25  Current 58 (34) 45 (26)  Previous 103 (61) 112 (66) Pack-years, median (IQR) 32.5 (20–50) 40 (20–55) 0.19 Alcoholism, n (%) 8 (5) 6 (3) 0.58 ECOG score >0, n (%) 15 (9) 14 (8) 0.85 COPD, n (%) 36 (21) 35 (21) 0.89 Charlson, mean ± SD 4.7 ± 1.7 4.7 ± 1.7 0.87 Neoadjuvant therapy, n (%) 12 (7) 11 (6) 0.83 Histology, n (%) 0.82  Adenocarcinoma 102 (60) 104 (61)  Squamous cell carcinoma 61 (36) 57 (33) Pneumonectomy, n (%) 5 (3) 4 (2) 0.73 Complete preoperative evaluation, n (%) 109 (64) 159 (93) <0.001 Advanced stages (III–IV), n (%) 41 (24) 26 (15) 0.04 Exploratory thoracotomy, n (%) 6 (3) 3 (1.8) 0.31 Completeness of resection, n (%) 157 (92.4) 160 (94.1) 0.52 Postoperative complications, n (%) 69 (40.6) 68 (40) 0.91 Postoperative mortality, n (%) 2 (1.2) 1 (0.6) 0.50 Variables Patients P-value Not discussed by MTB (n = 170) Discussed by MTB (n = 170) Gender, n (%)  Male 124 (73) 124 (73) 1.00  Female 46 (27) 46 (27) Age (years), mean ± SD 68.8 ± 8.4 68.9 ± 7.9 0.95 Smoke, n (%) 0.25  Current 58 (34) 45 (26)  Previous 103 (61) 112 (66) Pack-years, median (IQR) 32.5 (20–50) 40 (20–55) 0.19 Alcoholism, n (%) 8 (5) 6 (3) 0.58 ECOG score >0, n (%) 15 (9) 14 (8) 0.85 COPD, n (%) 36 (21) 35 (21) 0.89 Charlson, mean ± SD 4.7 ± 1.7 4.7 ± 1.7 0.87 Neoadjuvant therapy, n (%) 12 (7) 11 (6) 0.83 Histology, n (%) 0.82  Adenocarcinoma 102 (60) 104 (61)  Squamous cell carcinoma 61 (36) 57 (33) Pneumonectomy, n (%) 5 (3) 4 (2) 0.73 Complete preoperative evaluation, n (%) 109 (64) 159 (93) <0.001 Advanced stages (III–IV), n (%) 41 (24) 26 (15) 0.04 Exploratory thoracotomy, n (%) 6 (3) 3 (1.8) 0.31 Completeness of resection, n (%) 157 (92.4) 160 (94.1) 0.52 Postoperative complications, n (%) 69 (40.6) 68 (40) 0.91 Postoperative mortality, n (%) 2 (1.2) 1 (0.6) 0.50 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; MTB: multidisciplinary tumour board; SD: standard deviation. Table 2: Clinical data based on the propensity scores Variables Patients P-value Not discussed by MTB (n = 170) Discussed by MTB (n = 170) Gender, n (%)  Male 124 (73) 124 (73) 1.00  Female 46 (27) 46 (27) Age (years), mean ± SD 68.8 ± 8.4 68.9 ± 7.9 0.95 Smoke, n (%) 0.25  Current 58 (34) 45 (26)  Previous 103 (61) 112 (66) Pack-years, median (IQR) 32.5 (20–50) 40 (20–55) 0.19 Alcoholism, n (%) 8 (5) 6 (3) 0.58 ECOG score >0, n (%) 15 (9) 14 (8) 0.85 COPD, n (%) 36 (21) 35 (21) 0.89 Charlson, mean ± SD 4.7 ± 1.7 4.7 ± 1.7 0.87 Neoadjuvant therapy, n (%) 12 (7) 11 (6) 0.83 Histology, n (%) 0.82  Adenocarcinoma 102 (60) 104 (61)  Squamous cell carcinoma 61 (36) 57 (33) Pneumonectomy, n (%) 5 (3) 4 (2) 0.73 Complete preoperative evaluation, n (%) 109 (64) 159 (93) <0.001 Advanced stages (III–IV), n (%) 41 (24) 26 (15) 0.04 Exploratory thoracotomy, n (%) 6 (3) 3 (1.8) 0.31 Completeness of resection, n (%) 157 (92.4) 160 (94.1) 0.52 Postoperative complications, n (%) 69 (40.6) 68 (40) 0.91 Postoperative mortality, n (%) 2 (1.2) 1 (0.6) 0.50 Variables Patients P-value Not discussed by MTB (n = 170) Discussed by MTB (n = 170) Gender, n (%)  Male 124 (73) 124 (73) 1.00  Female 46 (27) 46 (27) Age (years), mean ± SD 68.8 ± 8.4 68.9 ± 7.9 0.95 Smoke, n (%) 0.25  Current 58 (34) 45 (26)  Previous 103 (61) 112 (66) Pack-years, median (IQR) 32.5 (20–50) 40 (20–55) 0.19 Alcoholism, n (%) 8 (5) 6 (3) 0.58 ECOG score >0, n (%) 15 (9) 14 (8) 0.85 COPD, n (%) 36 (21) 35 (21) 0.89 Charlson, mean ± SD 4.7 ± 1.7 4.7 ± 1.7 0.87 Neoadjuvant therapy, n (%) 12 (7) 11 (6) 0.83 Histology, n (%) 0.82  Adenocarcinoma 102 (60) 104 (61)  Squamous cell carcinoma 61 (36) 57 (33) Pneumonectomy, n (%) 5 (3) 4 (2) 0.73 Complete preoperative evaluation, n (%) 109 (64) 159 (93) <0.001 Advanced stages (III–IV), n (%) 41 (24) 26 (15) 0.04 Exploratory thoracotomy, n (%) 6 (3) 3 (1.8) 0.31 Completeness of resection, n (%) 157 (92.4) 160 (94.1) 0.52 Postoperative complications, n (%) 69 (40.6) 68 (40) 0.91 Postoperative mortality, n (%) 2 (1.2) 1 (0.6) 0.50 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; MTB: multidisciplinary tumour board; SD: standard deviation. Analysis of the propensity-matched groups for postoperative outcomes demonstrated that patients who were discussed at MTBs were associated with significantly lower advanced TNM stages: 26 (15%) patients who were discussed at MTBs before surgery were affected by Stages III and IV NSCLC, as compared to 41 (24%) patients who were not (P = 0.041). Furthermore, the MTB discussion group was associated with a higher rate of complete preoperative evaluation (P < 0.001). There was no difference in the incidence of exploratory thoracotomy, completeness of resection, postoperative complications and postoperative mortality. One-year mortality was significantly lower in the MTB group (18% vs 8% P = 0.006). The variables associated with 1-year mortality are listed in Table 3. Forty-three (13%) patients died within 1 year after the surgery. Table 3: Distribution of the variables according to 1-year survival Variables Patients P-value Alive (n = 297) Death (n = 43) Gender: male, n (%) 215 (72) 33 (77) 0.55 Age, mean ± SD 68.6 ± 8.1 70.6 ± 8.4 0.12 Smoke, n (%)  Current 90 (30) 13 (30) 0.17  Previous 185 (62) 30 (70) Pack-years, median (IQR) 35 (20–50) 40 (27–50) 0.18 Alcoholism, n (%) 11 (4) 3 (7) 0.25 Complete preoperative evaluation, n (%) 236 (80) 32 (74) 0.45 ECOG score >0, n (%) 20 (7) 9 (21) 0.005 Preoperative diagnosis, n (%) 169 (57) 25 (58) 0.88 COPD, n (%) 61 (20) 10 (23) 0.68 Charlson, n (%) 4.6 ± 1.7 5.4 ± 1.6 0.005 Advanced TNM stages (III–IV), n (%) 46 (15) 21 (49) <0.001 Neoadjuvant therapy, n (%) 17 (6) 6 (14) 0.055 Histology, n (%)  Adenocarcinoma 185 (62) 21 (49) 0.011  Squamous cell carcinoma 102 (34) 16 (37) Pneumonectomy, n (%) 8 (3) 1 (2) 0.68 Exploratory thoracotomy, n (%) 4 (1) 5 (12) 0.002 Complete resection, n (%) 280 (94) 37 (86) 0.055 Postoperative complications, n (%) 116 (39) 21 (49) 0.222 Mean hospital stay, median (IQR) 6 (4–7) 6 (4–8) 0.87 Variables Patients P-value Alive (n = 297) Death (n = 43) Gender: male, n (%) 215 (72) 33 (77) 0.55 Age, mean ± SD 68.6 ± 8.1 70.6 ± 8.4 0.12 Smoke, n (%)  Current 90 (30) 13 (30) 0.17  Previous 185 (62) 30 (70) Pack-years, median (IQR) 35 (20–50) 40 (27–50) 0.18 Alcoholism, n (%) 11 (4) 3 (7) 0.25 Complete preoperative evaluation, n (%) 236 (80) 32 (74) 0.45 ECOG score >0, n (%) 20 (7) 9 (21) 0.005 Preoperative diagnosis, n (%) 169 (57) 25 (58) 0.88 COPD, n (%) 61 (20) 10 (23) 0.68 Charlson, n (%) 4.6 ± 1.7 5.4 ± 1.6 0.005 Advanced TNM stages (III–IV), n (%) 46 (15) 21 (49) <0.001 Neoadjuvant therapy, n (%) 17 (6) 6 (14) 0.055 Histology, n (%)  Adenocarcinoma 185 (62) 21 (49) 0.011  Squamous cell carcinoma 102 (34) 16 (37) Pneumonectomy, n (%) 8 (3) 1 (2) 0.68 Exploratory thoracotomy, n (%) 4 (1) 5 (12) 0.002 Complete resection, n (%) 280 (94) 37 (86) 0.055 Postoperative complications, n (%) 116 (39) 21 (49) 0.222 Mean hospital stay, median (IQR) 6 (4–7) 6 (4–8) 0.87 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; SD: standard deviation; TNM: tumour, node and metastasis. Table 3: Distribution of the variables according to 1-year survival Variables Patients P-value Alive (n = 297) Death (n = 43) Gender: male, n (%) 215 (72) 33 (77) 0.55 Age, mean ± SD 68.6 ± 8.1 70.6 ± 8.4 0.12 Smoke, n (%)  Current 90 (30) 13 (30) 0.17  Previous 185 (62) 30 (70) Pack-years, median (IQR) 35 (20–50) 40 (27–50) 0.18 Alcoholism, n (%) 11 (4) 3 (7) 0.25 Complete preoperative evaluation, n (%) 236 (80) 32 (74) 0.45 ECOG score >0, n (%) 20 (7) 9 (21) 0.005 Preoperative diagnosis, n (%) 169 (57) 25 (58) 0.88 COPD, n (%) 61 (20) 10 (23) 0.68 Charlson, n (%) 4.6 ± 1.7 5.4 ± 1.6 0.005 Advanced TNM stages (III–IV), n (%) 46 (15) 21 (49) <0.001 Neoadjuvant therapy, n (%) 17 (6) 6 (14) 0.055 Histology, n (%)  Adenocarcinoma 185 (62) 21 (49) 0.011  Squamous cell carcinoma 102 (34) 16 (37) Pneumonectomy, n (%) 8 (3) 1 (2) 0.68 Exploratory thoracotomy, n (%) 4 (1) 5 (12) 0.002 Complete resection, n (%) 280 (94) 37 (86) 0.055 Postoperative complications, n (%) 116 (39) 21 (49) 0.222 Mean hospital stay, median (IQR) 6 (4–7) 6 (4–8) 0.87 Variables Patients P-value Alive (n = 297) Death (n = 43) Gender: male, n (%) 215 (72) 33 (77) 0.55 Age, mean ± SD 68.6 ± 8.1 70.6 ± 8.4 0.12 Smoke, n (%)  Current 90 (30) 13 (30) 0.17  Previous 185 (62) 30 (70) Pack-years, median (IQR) 35 (20–50) 40 (27–50) 0.18 Alcoholism, n (%) 11 (4) 3 (7) 0.25 Complete preoperative evaluation, n (%) 236 (80) 32 (74) 0.45 ECOG score >0, n (%) 20 (7) 9 (21) 0.005 Preoperative diagnosis, n (%) 169 (57) 25 (58) 0.88 COPD, n (%) 61 (20) 10 (23) 0.68 Charlson, n (%) 4.6 ± 1.7 5.4 ± 1.6 0.005 Advanced TNM stages (III–IV), n (%) 46 (15) 21 (49) <0.001 Neoadjuvant therapy, n (%) 17 (6) 6 (14) 0.055 Histology, n (%)  Adenocarcinoma 185 (62) 21 (49) 0.011  Squamous cell carcinoma 102 (34) 16 (37) Pneumonectomy, n (%) 8 (3) 1 (2) 0.68 Exploratory thoracotomy, n (%) 4 (1) 5 (12) 0.002 Complete resection, n (%) 280 (94) 37 (86) 0.055 Postoperative complications, n (%) 116 (39) 21 (49) 0.222 Mean hospital stay, median (IQR) 6 (4–7) 6 (4–8) 0.87 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; SD: standard deviation; TNM: tumour, node and metastasis. Performance status and patient comorbidities were significantly associated with negative 1-year survival rates in both groups. The factors such as patients with TNM Stages III and IV, non-therapeutic thoracotomy, postoperative complications, neoadjuvant therapies and completeness of resection were related to poor 1-year survival. Furthermore, patients who were treated within the thoracic malignancy care board and those who underwent a complete preoperative evaluation were found to have a significantly better 1-year survival when compared with patients diagnosed before the establishment of the conference. Follow-up and survival Figure 2 shows a Kaplan–Meier curve comparing the 2 groups. The Cox regression model was fitted to assess factors that were associated with survival: patients undergoing the MTB discussion were found to have a better 1-year survival (odds ratio 0.48; 95% confidence interval 0.25–0.92). Figure 2: View largeDownload slide The Kaplan–Meier plots on overall survival of patients whose cases were discussed, or were not discussed, at MTB meetings. MTB: multidisciplinary tumour board. Figure 2: View largeDownload slide The Kaplan–Meier plots on overall survival of patients whose cases were discussed, or were not discussed, at MTB meetings. MTB: multidisciplinary tumour board. DISCUSSION Patients affected by NSCLC require multimodal treatment with a combination of surgery, systemic chemotherapy and radiotherapy. This approach can have a palliative or curative intent and can involve multiple physicians and other healthcare professionals over the treatment period. The MTB provides an environment in which physicians and other healthcare professionals can discuss relevant diagnostic, pathological and therapeutic aspects of patient care [7]. The format of the MTB varies from roundtable discussions involving team members without the presence of the patient to a more hands-on approach in which the patient is present and is examined by the team members. Moreover, MTBs are now considered to be an integral part of the management of oncological patients in many tertiary care centres. In the UK, MTBs exist since 1995, and currently, more than 80% of cancer patients in the UK are assessed by an MTB, as compared to only 20% of patients a decade earlier [8–10]. Patients with malignancies other than lung cancer have also been shown to benefit from coordinated multidisciplinary care. Baldwin et al. [11] and Fairchild et al. [12] observed measurable benefits in the care of patients with breast cancer, including higher rates of breast conservation, multimodality therapy and pain management. Based on the previous discussion, it would seem intuitive that a prospective multidisciplinary care conference would benefit patients with lung cancer. However, challenges of implementing multidisciplinary care remain, and many centres must take responsibility to improve the process [13]. Furthermore, robust evidence to suggest improvement on outcomes in patients with NSCLC is lacking, which contributes to scepticism regarding MTB patient management. Our investigation sought to evaluate the impact of the MTB on survival by comparing 2 groups of patients with lung cancer treated by the same physicians at a tertiary care hospital before and after the establishment of an MTB. Few studies have evaluated MTBs for lung cancer, and most of them are focused on inoperable tumours. Ung et al. [14] assessed the impact of MTB meetings on patient management plans, and found that MTB recommendations on patient care were taken into consideration in 72% of cases. A prospective study by Leo et al. [15] involving 344 patients showed that patient discussion at MTBs led to discordance in 15 (4.4%) cases with a non-statistically significant trend toward an increase in survival in patients treated using a multidisciplinary care conference. Forrest et al. [16] compared survival in 2 groups of patients with inoperable lung cancer before and after implementation of a multidisciplinary team. The authors observed a significant increase in the number of patients receiving chemotherapy and an increased median survival after implementation of the team (3.2 months vs 6.6 months, P < 0.001). Similarly, Price et al. [17] observed a significant increase in radical radiotherapy administration and an improved 1-year survival rate (18.3% vs 23.5%) in patients with NSCLC after the introduction of MTBs. Another retrospective institutional review [18] showed that patients with advanced NSCLC evaluated at MTBs were more likely to receive chemoradiation and chemotherapy with a median survival benefit as compared to patients who were not (237 days vs 208 days). In contrast, Boxer et al. [19] analysed patient and tumour characteristics and treatment receipt in 988 cases treated for primary lung cancer. They observed that MTB discussion was related to better receipt of radiotherapy and chemotherapy in patients with stage IV NSCLC but did not influence survival. A prospective study involving 221 patients concluded that MTB does not improve the overall quality of clinical decision-making [20]. This study analysed the adherence to the treatment option provided by the lung cancer MTB and reported that in 50 cases, the treating physician did not follow the MTB’s recommendation, leading to the conclusion that the impact of team discussion was not significant. This study presents 2 principal findings. First, the proportion of patients undergoing complete preoperative investigations increased significantly following MTB introduction with a lower proportion of advanced stage cancer patients undergoing surgery. Second, a significant increase in survival for patients managed through the MTB was observed: a survival benefit of 92% after surgery with MTB discussion was found, as compared to 82% after surgery without MTB evaluation. Coory et al. [21] conducted a systematic review assessing the effectiveness of the MTB in lung cancer. Of the 16 studies that met the review inclusion criteria, only 2 reported that MTBs led to an improvement in survival. The authors concluded that current evidence on the MTB is stronger for improving patient management than for affecting survival. Although the MTB affects clinical decision-making, the results do not necessarily translate into improvements in patient care and overall survival. Multidisciplinary discussion provides an evidence-based approach to treat patients and care is standardized according to international guidelines and a positive environment allows clinicians to share their experience and knowledge [22]. The survival benefit was probably due to both the reduction in the number of advanced stage cancer patients proceeding to surgery, a more accurate selection of patients and the increased cumulative experience of the different specialists. These findings have led us to recommend the management of all cancer patients in an MTB at our institution, irrespective of staging. Limitations Although this study is unique in its design and subject, it does have some limitations. This investigation represents a single institution’s experience, the cohort of patients was assessed retrospectively, and we acknowledge that there is inherent bias associated with this approach. Prospective studies and analysis are required to test the role of this multidisciplinary approach in lung cancer patient treatment. Furthermore, the number of patients is relatively small, but the results nonetheless demonstrate what can be achieved by specialist care in a large district general hospital. CONCLUSION In conclusion, this study supports the view that multiprofessional lung cancer management improves the quality of care received by patients with NSCLC and the 1-year survival rate. Conflict of interest: none declared. REFERENCES 1 Deegan PC , Heath L , Brunskill J , Kinnear WJ , Morgan SA , Johnston ID. Reducing waiting times in lung cancer . J R Coll Physicians Lond 1998 ; 32 : 339 – 43 . Google Scholar PubMed 2 Oken MM , Creech RH , Tormey DC , Horton J , Davis TE , McFadden ET et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group . Am J Clin Oncol 1982 ; 5 : 649 – 55 . Google Scholar CrossRef Search ADS PubMed 3 Charlson ME , Pompei P , Ales KL , MacKenzie CR. A new method of classifying prognostic comorbidity in longitudinal studies: development and validation . J Chronic Dis 1987 ; 40 : 373 – 83 . Google Scholar CrossRef Search ADS PubMed 4 Ivanovic J , Al-Hussaini A , Al-Shehab D , Threader J , Villeneuve PJ , Ramsay T et al. Evaluating the reliability and reproducibility of the Ottawa Thoracic Morbidity and Mortality classification system . Ann Thorac Surg 2011 ; 91 : 387 – 93 . Google Scholar CrossRef Search ADS PubMed 5 Rami-Porta R , Crowley JJ , Goldstraw P. The revised TNM staging system for lung cancer . Ann Thorac Cardiovasc Surg 2009 ; 15 : 4 – 9 . Google Scholar PubMed 6 Martini N , Melamed MR. Multiple primary lung cancers . J Thorac Cardiovasc Surg 1975 ; 70 : 606 – 12 . Google Scholar PubMed 7 Wright FC , De Vito C , Langer B , Hunter A ; on behalf of the Expert Panel on Multidisciplinary Cancer Conference Standards . Multidisciplinary cancer conferences: a systematic review and development of practice standards . Eur J Cancer 2007 ; 43 : 1002 – 10 . Google Scholar CrossRef Search ADS PubMed 8 Tattersall MH. Multidisciplinary team meetings: where is the value? Lancet Oncol 2006 ; 7 : 886 – 8 . Google Scholar CrossRef Search ADS PubMed 9 Berrino F , Sant M , Verdecchia A , Capocaccia R , Hakulinen T , Estere J. Survival of Cancer Patients in Europe. The Eurocare Study . Lyon, France : World Health Organization, International Agency for Research on Cancer , 1995 . 10 Griffith C , Turner J. United Kingdom National Health Service, cancer services collaborative “improvement partnership”, redesign of cancer services: a national approach . Eur J Surg Oncol 2004 ; 30 : 1 – 86 . Google Scholar PubMed 11 Baldwin LM , Taplin SH , Friedman H , Moe R. Access to multidisciplinary cancer care: is it linked to the use of breast conserving surgery with radiation for early stage breast carcinoma? Cancer 2004 ; 100 : 701 – 9 . Google Scholar CrossRef Search ADS PubMed 12 Fairchild A , Pituskin E , Rose B , Ghosh S , Dutka J , Driga A et al. The rapid access palliative radiotherapy program: blueprint for initiation of a one-stop multidisciplinary bone metastases clinic . Support Care Cancer 2009 ; 17 : 163 – 70 . Google Scholar CrossRef Search ADS PubMed 13 Ellis PM. The importance of multidisciplinary team management of patients with non-small-cell lung cancer . Curr Oncol 2012 ; 19 : S7 – 15 . Google Scholar CrossRef Search ADS PubMed 14 Ung KA , Campbell BA , Duplan D , Ball D , David S. Impact of the lung oncology multidisciplinary team meetings on the management of patients with cancer . Asia Pac J Clin Oncol 2016 ; 12 : e298 – 304 . Google Scholar CrossRef Search ADS PubMed 15 Leo F , Venissac N , Poudenx M , Otto J , Mouroux J ; on behalf of Groupe d’Oncologie Thoracique Azuréen . Multidisciplinary management of lung cancer: how to test its efficacy? J Thorac Oncol 2007 ; 2 : 69 – 72 . Google Scholar CrossRef Search ADS PubMed 16 Forrest LM , McMillan DC , McArdle CS , Dunlop DJ. An evaluation of the impact of a multidisciplinary team, in a single centre, on treatment and survival in patients with inoperable non-small-cell lung cancer . Br J Cancer 2005 ; 93 : 977 – 8 . Google Scholar CrossRef Search ADS PubMed 17 Price A , Kerr G , Gregor A , Ironside J , Little F. The impact of multidisciplinary teams and site specialisation on the use of radiotherapy in elderly people with non-small cell lung cancer (NSCLC) . Radiother Oncol 2002 ; 64(suppl 1) : S80 . 18 Bydder S , Nowak A , Marion K , Phillips M , Atun R. The impact of case discussion at a multidisciplinary team meeting on the treatment and survival of patients with inoperable non-small cell lung cancer . Intern Med J 2009 ; 39 : 838 – 41 . Google Scholar CrossRef Search ADS PubMed 19 Boxer MM , Vinod SK , Shafiq J , Duggan KJ. Do multidisciplinary team meetings make a difference in the management of lung cancer? Cancer 2011 ; 117 : 5112 – 20 . Google Scholar CrossRef Search ADS PubMed 20 Kee F , Owen T , Leathem R. Decision making in a multidisciplinary cancer team: does team discussion result in better quality decisions? Med Decis Making 2004 ; 24 : 602 – 13 . Google Scholar CrossRef Search ADS PubMed 21 Coory M , Gkolia P , Yang IA , Bowman RV , Fong KM. Systematic review of multidisciplinary teams in the management of lung cancer . Lung Cancer 2008 ; 60 : 14 – 21 . Google Scholar CrossRef Search ADS PubMed 22 Oh IJ , Ahn SJ. Multidisciplinary team approach for the management of patients with locally advanced non-small cell lung cancer: searching the evidence to guide the decision . Radiat Oncol J 2017 ; 35 : 16 – 24 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Journal of Cardio-Thoracic Surgery Oxford University Press

Multidisciplinary management improves survival at 1 year after surgical treatment for non-small-cell lung cancer: a propensity score-matched study

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Oxford University Press
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© The Author(s) 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.
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1010-7940
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1873-734X
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10.1093/ejcts/ezx464
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Abstract

Abstract OBJECTIVES The management of patients affected by lung cancer requires the expertise of specialists from different disciplines. Although the advantages of multidisciplinary team discussions seem obvious, there are limited studies evaluating the influence of this approach on postoperative outcomes in non-small-cell lung cancer (NSCLC). The aim of this study is to examine the impact of a multidisciplinary approach on survival of patients undergoing surgery for NSCLC. METHODS A retrospective analysis was performed on consecutive patients who underwent surgery for NSCLC between January 2008 and December 2015. Data were compared between patients treated before the implementation of a multidisciplinary tumour board (MTB), between 2008 and 2012, and those who received treatment after the implementation of the MTB, between 2012 and 2015. Patients were matched one to one according to the discussion of the MTB and on the basis of a propensity score built using several patient characteristics. A propensity score-matched analysis was performed to compare patient outcomes. RESULTS A total of 246 patients were treated prior to the initiation of the MTB and 231 patients after the initiation of the MTB. Based on the propensity score, 2 well-matched groups of 170 patients were identified. Patients who were discussed at the MTB were noted to have better outcomes when compared with those who were not discussed at the MTB on different terms including complete staging evaluation, early tumour, node and metastasis (TNM) stages and 1-year survival rate. CONCLUSIONS Implementation of a multidisciplinary thoracic malignancy conference increased the 1-year survival rate of patients who underwent a surgical resection for NSCLC. Multidisciplinary approach, Quality of care, Surgical treatment, Multidisciplinary thoracic tumour board, Non-small-cell lung cancer, Patient outcome INTRODUCTION A multidisciplinary tumour board (MTB) brings together all teams involved in a patient’s care, including physicians (oncologists, radiologists, anaesthetists, surgeons, pulmonologists and pathologists), nurses, social workers, dieticians, physiotherapists and occupational therapists. The MTB members share their expertise, professional perspective and knowledge, and conferences are designed to enhance patient management and outcomes. Despite the absence of randomized trials, indirect evidence has shown a measureable improvement in outcomes since the introduction of multidisciplinary cancer care. However, the ability to measure the true effect of multidisciplinary care on cancer survival is limited by the inability to disentangle the effects of socioeconomic status, health service deprivation and heterogeneity of tumour stage from those secondary to implementation of a multidisciplinary approach and inherent improvements in cancer treatments over time. Although some data are available suggesting that managing lung cancer patients within an MTB results in timely access to treatment and adherence to guidelines, to date, specific evidence is not available regarding the impact of this model of lung cancer care on survival or patient satisfaction [1]. The aim of this study is to evaluate the impact of lung cancer MTB on different outcomes including 1-year survival by comparing patients treated before and after the establishment of a prospective, multidisciplinary care conference. METHODS Study design and population This study was conducted at the Ferrara University Hospital, which is a tertiary centre for thoracic surgery. A multidisciplinary thoracic tumour board responsible for the management of patients with known or suspected lung, pleural or mediastinal malignancies was established in 2012. The MTB meeting is held weekly and attendees include surgeons, pulmonary oncologists, radiation oncologists, radiologists, nuclear medicine specialists, pulmonologists, pathologists, lung cancer care coordinators and trainees. A management strategy is formulated and documented for each patient at the MTB meeting. An MTB database is created to assist with patient management. The data collected include patient demographics, smoking and occupational exposures, clinical parameters, patient performance status and comorbidities, tumour characteristics, treatment methods and survival. This retrospective cohort analysis is performed with the permission of the institutional ethics board. All consecutive patients who underwent surgery with curative intent for non-small-cell lung cancer (NSCLC) at our department between January 2008 and December 2015 were identified using the MTB and institution’s database. A retrospective analysis of these patient records was performed. Demographic data, completeness of staging, multidisciplinary evaluation prior to the initiation of therapy, preoperative diagnosis, pathological stages, surgical procedure, completeness of resection, hospital stay, postoperative complications and 1-year survival were all assessed. Overall survival was calculated from the day of surgery. Performance status was classified according to the Eastern Co-operative Oncology Group (ECOG) score [2] and comorbidities and postoperative complications were defined according to the Charlson Comorbidity Index Score [3] and the Ottawa thoracic morbidity and mortality classification system score [4], respectively. During the period under evaluation, the seventh edition of the tumour, node and metastasis (TNM) staging system replaced the sixth edition. Therefore, for this analysis, all patients were restaged using the seventh edition of the TNM staging system [5] based on information from bronchoscopy/endobronchial ultrasound/oesophageal ultrasound, computed tomography scan, fluorodeoxyglucose-positron emission tomography scan and a magnetic resonance imaging or computed tomography of the brain and the final pathology report. Two study groups were identified based on whether patients had their care prospectively coordinated through the institution’s multidisciplinary thoracic malignancy care conference or were treated prior to the conference’s implementation. Exclusion criteria included patient refusal of treatment following diagnosis, patients with superior sulcus tumours, patients undergoing surgery for NSCLC metastasis according to the Martini and Metamed criteria [6] and patients undergoing surgery with diagnostic or palliative intent. Complete preoperative evaluation The minimum preoperative evaluation was defined as a minimum of computed tomography scan, including the chest, upper abdomen and adrenal glands, positron emission tomography, bronchoscopy, complete blood count, electrolyte profile, pulmonary function tests and further evaluation of any specific symptoms. Statistical analysis Propensity score matching was performed to create 2 groups with no difference with respect to confounding factors. Propensity score was estimated using the logistic regression model with discussion of the MTB as the outcome. The following explanatory variables were included in the analysis: age, sex, the ECOG score >0, the Charlson Comorbidity Index, neoadjuvant therapy and pneumonectomy (Table 1). Patients were matched using the ‘nearest neighbour’ procedure with a maximum difference in propensity score of 10% of its standard deviation. Table 1: Clinical characteristics of the 2 cohorts of lung cancer patients identified for propensity score matching Variables Patients P-value Not discussed by MTB (n = 246) Discussed by MTB (n = 186) Gender, n (%) 189 (77) 128 (69) 0.05 Age (years), mean ± SD 69.9 ± 8.3 68.1 ± 8.2 0.02 Smoke, n (%) 0.53  Current 72 (30) 49 (26)  Previous 159 (65) 121 (65) Pack-years, median (IQR) 35 (20–50) 40 (20–52) 0.29 Alcoholism, n (%) 13 (5) 7 (4) 0.31 ECOG score >0, n (%) 24 (10) 14 (7) 0.42 COPD, n (%) 53 (21) 38 (20) 0.78 Charlson, mean ± SD 4.8 ± 1.6 4.7 ± 1.7 0.47 Neoadjuvant therapy, n (%) 19 (8) 12 (6) 0.61 Histology, n (%) 0.84  Adenocarcinoma 151 (61) 119 (64)  Squamous cell carcinoma 81 (33) 58 (31) Adjuvant therapy, n (%) 50 (20) 25 (13) 0.29 VATS, n (%) 22 (9) 89 (48) 0.001 Variables Patients P-value Not discussed by MTB (n = 246) Discussed by MTB (n = 186) Gender, n (%) 189 (77) 128 (69) 0.05 Age (years), mean ± SD 69.9 ± 8.3 68.1 ± 8.2 0.02 Smoke, n (%) 0.53  Current 72 (30) 49 (26)  Previous 159 (65) 121 (65) Pack-years, median (IQR) 35 (20–50) 40 (20–52) 0.29 Alcoholism, n (%) 13 (5) 7 (4) 0.31 ECOG score >0, n (%) 24 (10) 14 (7) 0.42 COPD, n (%) 53 (21) 38 (20) 0.78 Charlson, mean ± SD 4.8 ± 1.6 4.7 ± 1.7 0.47 Neoadjuvant therapy, n (%) 19 (8) 12 (6) 0.61 Histology, n (%) 0.84  Adenocarcinoma 151 (61) 119 (64)  Squamous cell carcinoma 81 (33) 58 (31) Adjuvant therapy, n (%) 50 (20) 25 (13) 0.29 VATS, n (%) 22 (9) 89 (48) 0.001 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; MTB: multidisciplinary tumour board; SD: standard deviation; VATS: video-assisted thoracoscopic surgery. Table 1: Clinical characteristics of the 2 cohorts of lung cancer patients identified for propensity score matching Variables Patients P-value Not discussed by MTB (n = 246) Discussed by MTB (n = 186) Gender, n (%) 189 (77) 128 (69) 0.05 Age (years), mean ± SD 69.9 ± 8.3 68.1 ± 8.2 0.02 Smoke, n (%) 0.53  Current 72 (30) 49 (26)  Previous 159 (65) 121 (65) Pack-years, median (IQR) 35 (20–50) 40 (20–52) 0.29 Alcoholism, n (%) 13 (5) 7 (4) 0.31 ECOG score >0, n (%) 24 (10) 14 (7) 0.42 COPD, n (%) 53 (21) 38 (20) 0.78 Charlson, mean ± SD 4.8 ± 1.6 4.7 ± 1.7 0.47 Neoadjuvant therapy, n (%) 19 (8) 12 (6) 0.61 Histology, n (%) 0.84  Adenocarcinoma 151 (61) 119 (64)  Squamous cell carcinoma 81 (33) 58 (31) Adjuvant therapy, n (%) 50 (20) 25 (13) 0.29 VATS, n (%) 22 (9) 89 (48) 0.001 Variables Patients P-value Not discussed by MTB (n = 246) Discussed by MTB (n = 186) Gender, n (%) 189 (77) 128 (69) 0.05 Age (years), mean ± SD 69.9 ± 8.3 68.1 ± 8.2 0.02 Smoke, n (%) 0.53  Current 72 (30) 49 (26)  Previous 159 (65) 121 (65) Pack-years, median (IQR) 35 (20–50) 40 (20–52) 0.29 Alcoholism, n (%) 13 (5) 7 (4) 0.31 ECOG score >0, n (%) 24 (10) 14 (7) 0.42 COPD, n (%) 53 (21) 38 (20) 0.78 Charlson, mean ± SD 4.8 ± 1.6 4.7 ± 1.7 0.47 Neoadjuvant therapy, n (%) 19 (8) 12 (6) 0.61 Histology, n (%) 0.84  Adenocarcinoma 151 (61) 119 (64)  Squamous cell carcinoma 81 (33) 58 (31) Adjuvant therapy, n (%) 50 (20) 25 (13) 0.29 VATS, n (%) 22 (9) 89 (48) 0.001 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; MTB: multidisciplinary tumour board; SD: standard deviation; VATS: video-assisted thoracoscopic surgery. Continuous data were expressed as means ± standard deviation or as median and interquartile range (IQR), whereas categorical variables were summarized as absolute frequencies and percentages. After propensity score matching was performed, differences between the 2 groups (MTB no/yes and alive/deceased after 1 year) were assessed using the χ2 test or the Fisher’s exact test for categorical variables and the Student’s t-test or the non-parametric Mann–Whitney U-test for continuous data, as appropriate. To evaluate the significance of the MTB discussion as a factor for the outcome of 1-year mortality after surgical treatment, a simple Cox regression model was carried out. To measure the net effect of the MTB, the model was then adjusted adding on the variables that were significantly associated with death. Finally, unnecessary variables were removed using a stepwise backward selection technique (P-value for removal = 0.1), and a more parsimonious multiple model was obtained; hazard ratios and their 95% confidence interval were reported. Results were considered statistically significant at P < 0.05. All analyses were performed using R version 3.4.0 (R Core Team (2017)) and Stata 13.0 for Windows (StataCorp, College Station, TX, USA). RESULTS Patient and treatment characteristics In total, 488 consecutive patients with NSCLC were treated and included in this study. Eleven patients were excluded because of lack of patients’ charts. In the remaining 477 patients, 246 were treated before the MTB implementation and 231 patients underwent surgery after the MTB discussion, 45 of whom were treated after 2012 without the MTB evaluation and were, therefore, excluded from our analysis. During the study period, an increased proportion of cases undergoing surgery for lung cancer was presented at the MTB meeting (Fig. 1): in 2015, 92% of cases were presented during the MTB meeting, whereas in 2012, only 46% of cases were discussed. Figure 1: View largeDownload slide Proportion of patients presented at MTB meetings (blue) before surgery between 2012 and 2015. MTB: multidisciplinary tumour board. Figure 1: View largeDownload slide Proportion of patients presented at MTB meetings (blue) before surgery between 2012 and 2015. MTB: multidisciplinary tumour board. Demographic data for the 2 groups are summarized in Table 1. In the MTB discussion group, a lower proportion of men and mean age can be noted. Furthermore, significantly more patients in the MTB group underwent lung resection by video-assisted thoracoscopic surgery when compared with the non-MTB group (48% vs 9%). All the other variables were comparable between the 2 groups. Specifically, the distribution of tumour histology, smoking history and chronic obstructive pulmonary disease did not differ significantly between the 2 groups. The mean Charlson Comorbidity Index was 4.7, and a similar proportion of patients undergoing neoadjuvant and adjuvant treatments was observed in both groups. Two homogeneous groups of 170 patients each (the no MTB discussion and MTB discussion groups) were identified based on the propensity score including 6 different variables. The demographic, clinical and histological characteristics of both groups are summarized in Table 2. Table 2: Clinical data based on the propensity scores Variables Patients P-value Not discussed by MTB (n = 170) Discussed by MTB (n = 170) Gender, n (%)  Male 124 (73) 124 (73) 1.00  Female 46 (27) 46 (27) Age (years), mean ± SD 68.8 ± 8.4 68.9 ± 7.9 0.95 Smoke, n (%) 0.25  Current 58 (34) 45 (26)  Previous 103 (61) 112 (66) Pack-years, median (IQR) 32.5 (20–50) 40 (20–55) 0.19 Alcoholism, n (%) 8 (5) 6 (3) 0.58 ECOG score >0, n (%) 15 (9) 14 (8) 0.85 COPD, n (%) 36 (21) 35 (21) 0.89 Charlson, mean ± SD 4.7 ± 1.7 4.7 ± 1.7 0.87 Neoadjuvant therapy, n (%) 12 (7) 11 (6) 0.83 Histology, n (%) 0.82  Adenocarcinoma 102 (60) 104 (61)  Squamous cell carcinoma 61 (36) 57 (33) Pneumonectomy, n (%) 5 (3) 4 (2) 0.73 Complete preoperative evaluation, n (%) 109 (64) 159 (93) <0.001 Advanced stages (III–IV), n (%) 41 (24) 26 (15) 0.04 Exploratory thoracotomy, n (%) 6 (3) 3 (1.8) 0.31 Completeness of resection, n (%) 157 (92.4) 160 (94.1) 0.52 Postoperative complications, n (%) 69 (40.6) 68 (40) 0.91 Postoperative mortality, n (%) 2 (1.2) 1 (0.6) 0.50 Variables Patients P-value Not discussed by MTB (n = 170) Discussed by MTB (n = 170) Gender, n (%)  Male 124 (73) 124 (73) 1.00  Female 46 (27) 46 (27) Age (years), mean ± SD 68.8 ± 8.4 68.9 ± 7.9 0.95 Smoke, n (%) 0.25  Current 58 (34) 45 (26)  Previous 103 (61) 112 (66) Pack-years, median (IQR) 32.5 (20–50) 40 (20–55) 0.19 Alcoholism, n (%) 8 (5) 6 (3) 0.58 ECOG score >0, n (%) 15 (9) 14 (8) 0.85 COPD, n (%) 36 (21) 35 (21) 0.89 Charlson, mean ± SD 4.7 ± 1.7 4.7 ± 1.7 0.87 Neoadjuvant therapy, n (%) 12 (7) 11 (6) 0.83 Histology, n (%) 0.82  Adenocarcinoma 102 (60) 104 (61)  Squamous cell carcinoma 61 (36) 57 (33) Pneumonectomy, n (%) 5 (3) 4 (2) 0.73 Complete preoperative evaluation, n (%) 109 (64) 159 (93) <0.001 Advanced stages (III–IV), n (%) 41 (24) 26 (15) 0.04 Exploratory thoracotomy, n (%) 6 (3) 3 (1.8) 0.31 Completeness of resection, n (%) 157 (92.4) 160 (94.1) 0.52 Postoperative complications, n (%) 69 (40.6) 68 (40) 0.91 Postoperative mortality, n (%) 2 (1.2) 1 (0.6) 0.50 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; MTB: multidisciplinary tumour board; SD: standard deviation. Table 2: Clinical data based on the propensity scores Variables Patients P-value Not discussed by MTB (n = 170) Discussed by MTB (n = 170) Gender, n (%)  Male 124 (73) 124 (73) 1.00  Female 46 (27) 46 (27) Age (years), mean ± SD 68.8 ± 8.4 68.9 ± 7.9 0.95 Smoke, n (%) 0.25  Current 58 (34) 45 (26)  Previous 103 (61) 112 (66) Pack-years, median (IQR) 32.5 (20–50) 40 (20–55) 0.19 Alcoholism, n (%) 8 (5) 6 (3) 0.58 ECOG score >0, n (%) 15 (9) 14 (8) 0.85 COPD, n (%) 36 (21) 35 (21) 0.89 Charlson, mean ± SD 4.7 ± 1.7 4.7 ± 1.7 0.87 Neoadjuvant therapy, n (%) 12 (7) 11 (6) 0.83 Histology, n (%) 0.82  Adenocarcinoma 102 (60) 104 (61)  Squamous cell carcinoma 61 (36) 57 (33) Pneumonectomy, n (%) 5 (3) 4 (2) 0.73 Complete preoperative evaluation, n (%) 109 (64) 159 (93) <0.001 Advanced stages (III–IV), n (%) 41 (24) 26 (15) 0.04 Exploratory thoracotomy, n (%) 6 (3) 3 (1.8) 0.31 Completeness of resection, n (%) 157 (92.4) 160 (94.1) 0.52 Postoperative complications, n (%) 69 (40.6) 68 (40) 0.91 Postoperative mortality, n (%) 2 (1.2) 1 (0.6) 0.50 Variables Patients P-value Not discussed by MTB (n = 170) Discussed by MTB (n = 170) Gender, n (%)  Male 124 (73) 124 (73) 1.00  Female 46 (27) 46 (27) Age (years), mean ± SD 68.8 ± 8.4 68.9 ± 7.9 0.95 Smoke, n (%) 0.25  Current 58 (34) 45 (26)  Previous 103 (61) 112 (66) Pack-years, median (IQR) 32.5 (20–50) 40 (20–55) 0.19 Alcoholism, n (%) 8 (5) 6 (3) 0.58 ECOG score >0, n (%) 15 (9) 14 (8) 0.85 COPD, n (%) 36 (21) 35 (21) 0.89 Charlson, mean ± SD 4.7 ± 1.7 4.7 ± 1.7 0.87 Neoadjuvant therapy, n (%) 12 (7) 11 (6) 0.83 Histology, n (%) 0.82  Adenocarcinoma 102 (60) 104 (61)  Squamous cell carcinoma 61 (36) 57 (33) Pneumonectomy, n (%) 5 (3) 4 (2) 0.73 Complete preoperative evaluation, n (%) 109 (64) 159 (93) <0.001 Advanced stages (III–IV), n (%) 41 (24) 26 (15) 0.04 Exploratory thoracotomy, n (%) 6 (3) 3 (1.8) 0.31 Completeness of resection, n (%) 157 (92.4) 160 (94.1) 0.52 Postoperative complications, n (%) 69 (40.6) 68 (40) 0.91 Postoperative mortality, n (%) 2 (1.2) 1 (0.6) 0.50 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; MTB: multidisciplinary tumour board; SD: standard deviation. Analysis of the propensity-matched groups for postoperative outcomes demonstrated that patients who were discussed at MTBs were associated with significantly lower advanced TNM stages: 26 (15%) patients who were discussed at MTBs before surgery were affected by Stages III and IV NSCLC, as compared to 41 (24%) patients who were not (P = 0.041). Furthermore, the MTB discussion group was associated with a higher rate of complete preoperative evaluation (P < 0.001). There was no difference in the incidence of exploratory thoracotomy, completeness of resection, postoperative complications and postoperative mortality. One-year mortality was significantly lower in the MTB group (18% vs 8% P = 0.006). The variables associated with 1-year mortality are listed in Table 3. Forty-three (13%) patients died within 1 year after the surgery. Table 3: Distribution of the variables according to 1-year survival Variables Patients P-value Alive (n = 297) Death (n = 43) Gender: male, n (%) 215 (72) 33 (77) 0.55 Age, mean ± SD 68.6 ± 8.1 70.6 ± 8.4 0.12 Smoke, n (%)  Current 90 (30) 13 (30) 0.17  Previous 185 (62) 30 (70) Pack-years, median (IQR) 35 (20–50) 40 (27–50) 0.18 Alcoholism, n (%) 11 (4) 3 (7) 0.25 Complete preoperative evaluation, n (%) 236 (80) 32 (74) 0.45 ECOG score >0, n (%) 20 (7) 9 (21) 0.005 Preoperative diagnosis, n (%) 169 (57) 25 (58) 0.88 COPD, n (%) 61 (20) 10 (23) 0.68 Charlson, n (%) 4.6 ± 1.7 5.4 ± 1.6 0.005 Advanced TNM stages (III–IV), n (%) 46 (15) 21 (49) <0.001 Neoadjuvant therapy, n (%) 17 (6) 6 (14) 0.055 Histology, n (%)  Adenocarcinoma 185 (62) 21 (49) 0.011  Squamous cell carcinoma 102 (34) 16 (37) Pneumonectomy, n (%) 8 (3) 1 (2) 0.68 Exploratory thoracotomy, n (%) 4 (1) 5 (12) 0.002 Complete resection, n (%) 280 (94) 37 (86) 0.055 Postoperative complications, n (%) 116 (39) 21 (49) 0.222 Mean hospital stay, median (IQR) 6 (4–7) 6 (4–8) 0.87 Variables Patients P-value Alive (n = 297) Death (n = 43) Gender: male, n (%) 215 (72) 33 (77) 0.55 Age, mean ± SD 68.6 ± 8.1 70.6 ± 8.4 0.12 Smoke, n (%)  Current 90 (30) 13 (30) 0.17  Previous 185 (62) 30 (70) Pack-years, median (IQR) 35 (20–50) 40 (27–50) 0.18 Alcoholism, n (%) 11 (4) 3 (7) 0.25 Complete preoperative evaluation, n (%) 236 (80) 32 (74) 0.45 ECOG score >0, n (%) 20 (7) 9 (21) 0.005 Preoperative diagnosis, n (%) 169 (57) 25 (58) 0.88 COPD, n (%) 61 (20) 10 (23) 0.68 Charlson, n (%) 4.6 ± 1.7 5.4 ± 1.6 0.005 Advanced TNM stages (III–IV), n (%) 46 (15) 21 (49) <0.001 Neoadjuvant therapy, n (%) 17 (6) 6 (14) 0.055 Histology, n (%)  Adenocarcinoma 185 (62) 21 (49) 0.011  Squamous cell carcinoma 102 (34) 16 (37) Pneumonectomy, n (%) 8 (3) 1 (2) 0.68 Exploratory thoracotomy, n (%) 4 (1) 5 (12) 0.002 Complete resection, n (%) 280 (94) 37 (86) 0.055 Postoperative complications, n (%) 116 (39) 21 (49) 0.222 Mean hospital stay, median (IQR) 6 (4–7) 6 (4–8) 0.87 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; SD: standard deviation; TNM: tumour, node and metastasis. Table 3: Distribution of the variables according to 1-year survival Variables Patients P-value Alive (n = 297) Death (n = 43) Gender: male, n (%) 215 (72) 33 (77) 0.55 Age, mean ± SD 68.6 ± 8.1 70.6 ± 8.4 0.12 Smoke, n (%)  Current 90 (30) 13 (30) 0.17  Previous 185 (62) 30 (70) Pack-years, median (IQR) 35 (20–50) 40 (27–50) 0.18 Alcoholism, n (%) 11 (4) 3 (7) 0.25 Complete preoperative evaluation, n (%) 236 (80) 32 (74) 0.45 ECOG score >0, n (%) 20 (7) 9 (21) 0.005 Preoperative diagnosis, n (%) 169 (57) 25 (58) 0.88 COPD, n (%) 61 (20) 10 (23) 0.68 Charlson, n (%) 4.6 ± 1.7 5.4 ± 1.6 0.005 Advanced TNM stages (III–IV), n (%) 46 (15) 21 (49) <0.001 Neoadjuvant therapy, n (%) 17 (6) 6 (14) 0.055 Histology, n (%)  Adenocarcinoma 185 (62) 21 (49) 0.011  Squamous cell carcinoma 102 (34) 16 (37) Pneumonectomy, n (%) 8 (3) 1 (2) 0.68 Exploratory thoracotomy, n (%) 4 (1) 5 (12) 0.002 Complete resection, n (%) 280 (94) 37 (86) 0.055 Postoperative complications, n (%) 116 (39) 21 (49) 0.222 Mean hospital stay, median (IQR) 6 (4–7) 6 (4–8) 0.87 Variables Patients P-value Alive (n = 297) Death (n = 43) Gender: male, n (%) 215 (72) 33 (77) 0.55 Age, mean ± SD 68.6 ± 8.1 70.6 ± 8.4 0.12 Smoke, n (%)  Current 90 (30) 13 (30) 0.17  Previous 185 (62) 30 (70) Pack-years, median (IQR) 35 (20–50) 40 (27–50) 0.18 Alcoholism, n (%) 11 (4) 3 (7) 0.25 Complete preoperative evaluation, n (%) 236 (80) 32 (74) 0.45 ECOG score >0, n (%) 20 (7) 9 (21) 0.005 Preoperative diagnosis, n (%) 169 (57) 25 (58) 0.88 COPD, n (%) 61 (20) 10 (23) 0.68 Charlson, n (%) 4.6 ± 1.7 5.4 ± 1.6 0.005 Advanced TNM stages (III–IV), n (%) 46 (15) 21 (49) <0.001 Neoadjuvant therapy, n (%) 17 (6) 6 (14) 0.055 Histology, n (%)  Adenocarcinoma 185 (62) 21 (49) 0.011  Squamous cell carcinoma 102 (34) 16 (37) Pneumonectomy, n (%) 8 (3) 1 (2) 0.68 Exploratory thoracotomy, n (%) 4 (1) 5 (12) 0.002 Complete resection, n (%) 280 (94) 37 (86) 0.055 Postoperative complications, n (%) 116 (39) 21 (49) 0.222 Mean hospital stay, median (IQR) 6 (4–7) 6 (4–8) 0.87 COPD: chronic obstructive pulmonary disease; ECOG: Eastern Co-operative Oncology Group; IQR: interquartile range; SD: standard deviation; TNM: tumour, node and metastasis. Performance status and patient comorbidities were significantly associated with negative 1-year survival rates in both groups. The factors such as patients with TNM Stages III and IV, non-therapeutic thoracotomy, postoperative complications, neoadjuvant therapies and completeness of resection were related to poor 1-year survival. Furthermore, patients who were treated within the thoracic malignancy care board and those who underwent a complete preoperative evaluation were found to have a significantly better 1-year survival when compared with patients diagnosed before the establishment of the conference. Follow-up and survival Figure 2 shows a Kaplan–Meier curve comparing the 2 groups. The Cox regression model was fitted to assess factors that were associated with survival: patients undergoing the MTB discussion were found to have a better 1-year survival (odds ratio 0.48; 95% confidence interval 0.25–0.92). Figure 2: View largeDownload slide The Kaplan–Meier plots on overall survival of patients whose cases were discussed, or were not discussed, at MTB meetings. MTB: multidisciplinary tumour board. Figure 2: View largeDownload slide The Kaplan–Meier plots on overall survival of patients whose cases were discussed, or were not discussed, at MTB meetings. MTB: multidisciplinary tumour board. DISCUSSION Patients affected by NSCLC require multimodal treatment with a combination of surgery, systemic chemotherapy and radiotherapy. This approach can have a palliative or curative intent and can involve multiple physicians and other healthcare professionals over the treatment period. The MTB provides an environment in which physicians and other healthcare professionals can discuss relevant diagnostic, pathological and therapeutic aspects of patient care [7]. The format of the MTB varies from roundtable discussions involving team members without the presence of the patient to a more hands-on approach in which the patient is present and is examined by the team members. Moreover, MTBs are now considered to be an integral part of the management of oncological patients in many tertiary care centres. In the UK, MTBs exist since 1995, and currently, more than 80% of cancer patients in the UK are assessed by an MTB, as compared to only 20% of patients a decade earlier [8–10]. Patients with malignancies other than lung cancer have also been shown to benefit from coordinated multidisciplinary care. Baldwin et al. [11] and Fairchild et al. [12] observed measurable benefits in the care of patients with breast cancer, including higher rates of breast conservation, multimodality therapy and pain management. Based on the previous discussion, it would seem intuitive that a prospective multidisciplinary care conference would benefit patients with lung cancer. However, challenges of implementing multidisciplinary care remain, and many centres must take responsibility to improve the process [13]. Furthermore, robust evidence to suggest improvement on outcomes in patients with NSCLC is lacking, which contributes to scepticism regarding MTB patient management. Our investigation sought to evaluate the impact of the MTB on survival by comparing 2 groups of patients with lung cancer treated by the same physicians at a tertiary care hospital before and after the establishment of an MTB. Few studies have evaluated MTBs for lung cancer, and most of them are focused on inoperable tumours. Ung et al. [14] assessed the impact of MTB meetings on patient management plans, and found that MTB recommendations on patient care were taken into consideration in 72% of cases. A prospective study by Leo et al. [15] involving 344 patients showed that patient discussion at MTBs led to discordance in 15 (4.4%) cases with a non-statistically significant trend toward an increase in survival in patients treated using a multidisciplinary care conference. Forrest et al. [16] compared survival in 2 groups of patients with inoperable lung cancer before and after implementation of a multidisciplinary team. The authors observed a significant increase in the number of patients receiving chemotherapy and an increased median survival after implementation of the team (3.2 months vs 6.6 months, P < 0.001). Similarly, Price et al. [17] observed a significant increase in radical radiotherapy administration and an improved 1-year survival rate (18.3% vs 23.5%) in patients with NSCLC after the introduction of MTBs. Another retrospective institutional review [18] showed that patients with advanced NSCLC evaluated at MTBs were more likely to receive chemoradiation and chemotherapy with a median survival benefit as compared to patients who were not (237 days vs 208 days). In contrast, Boxer et al. [19] analysed patient and tumour characteristics and treatment receipt in 988 cases treated for primary lung cancer. They observed that MTB discussion was related to better receipt of radiotherapy and chemotherapy in patients with stage IV NSCLC but did not influence survival. A prospective study involving 221 patients concluded that MTB does not improve the overall quality of clinical decision-making [20]. This study analysed the adherence to the treatment option provided by the lung cancer MTB and reported that in 50 cases, the treating physician did not follow the MTB’s recommendation, leading to the conclusion that the impact of team discussion was not significant. This study presents 2 principal findings. First, the proportion of patients undergoing complete preoperative investigations increased significantly following MTB introduction with a lower proportion of advanced stage cancer patients undergoing surgery. Second, a significant increase in survival for patients managed through the MTB was observed: a survival benefit of 92% after surgery with MTB discussion was found, as compared to 82% after surgery without MTB evaluation. Coory et al. [21] conducted a systematic review assessing the effectiveness of the MTB in lung cancer. Of the 16 studies that met the review inclusion criteria, only 2 reported that MTBs led to an improvement in survival. The authors concluded that current evidence on the MTB is stronger for improving patient management than for affecting survival. Although the MTB affects clinical decision-making, the results do not necessarily translate into improvements in patient care and overall survival. Multidisciplinary discussion provides an evidence-based approach to treat patients and care is standardized according to international guidelines and a positive environment allows clinicians to share their experience and knowledge [22]. The survival benefit was probably due to both the reduction in the number of advanced stage cancer patients proceeding to surgery, a more accurate selection of patients and the increased cumulative experience of the different specialists. These findings have led us to recommend the management of all cancer patients in an MTB at our institution, irrespective of staging. Limitations Although this study is unique in its design and subject, it does have some limitations. This investigation represents a single institution’s experience, the cohort of patients was assessed retrospectively, and we acknowledge that there is inherent bias associated with this approach. Prospective studies and analysis are required to test the role of this multidisciplinary approach in lung cancer patient treatment. Furthermore, the number of patients is relatively small, but the results nonetheless demonstrate what can be achieved by specialist care in a large district general hospital. CONCLUSION In conclusion, this study supports the view that multiprofessional lung cancer management improves the quality of care received by patients with NSCLC and the 1-year survival rate. Conflict of interest: none declared. REFERENCES 1 Deegan PC , Heath L , Brunskill J , Kinnear WJ , Morgan SA , Johnston ID. Reducing waiting times in lung cancer . J R Coll Physicians Lond 1998 ; 32 : 339 – 43 . Google Scholar PubMed 2 Oken MM , Creech RH , Tormey DC , Horton J , Davis TE , McFadden ET et al. Toxicity and response criteria of the Eastern Cooperative Oncology Group . Am J Clin Oncol 1982 ; 5 : 649 – 55 . 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Cancer 2004 ; 100 : 701 – 9 . Google Scholar CrossRef Search ADS PubMed 12 Fairchild A , Pituskin E , Rose B , Ghosh S , Dutka J , Driga A et al. The rapid access palliative radiotherapy program: blueprint for initiation of a one-stop multidisciplinary bone metastases clinic . Support Care Cancer 2009 ; 17 : 163 – 70 . Google Scholar CrossRef Search ADS PubMed 13 Ellis PM. The importance of multidisciplinary team management of patients with non-small-cell lung cancer . Curr Oncol 2012 ; 19 : S7 – 15 . Google Scholar CrossRef Search ADS PubMed 14 Ung KA , Campbell BA , Duplan D , Ball D , David S. Impact of the lung oncology multidisciplinary team meetings on the management of patients with cancer . Asia Pac J Clin Oncol 2016 ; 12 : e298 – 304 . Google Scholar CrossRef Search ADS PubMed 15 Leo F , Venissac N , Poudenx M , Otto J , Mouroux J ; on behalf of Groupe d’Oncologie Thoracique Azuréen . Multidisciplinary management of lung cancer: how to test its efficacy? J Thorac Oncol 2007 ; 2 : 69 – 72 . Google Scholar CrossRef Search ADS PubMed 16 Forrest LM , McMillan DC , McArdle CS , Dunlop DJ. An evaluation of the impact of a multidisciplinary team, in a single centre, on treatment and survival in patients with inoperable non-small-cell lung cancer . Br J Cancer 2005 ; 93 : 977 – 8 . Google Scholar CrossRef Search ADS PubMed 17 Price A , Kerr G , Gregor A , Ironside J , Little F. The impact of multidisciplinary teams and site specialisation on the use of radiotherapy in elderly people with non-small cell lung cancer (NSCLC) . Radiother Oncol 2002 ; 64(suppl 1) : S80 . 18 Bydder S , Nowak A , Marion K , Phillips M , Atun R. The impact of case discussion at a multidisciplinary team meeting on the treatment and survival of patients with inoperable non-small cell lung cancer . Intern Med J 2009 ; 39 : 838 – 41 . Google Scholar CrossRef Search ADS PubMed 19 Boxer MM , Vinod SK , Shafiq J , Duggan KJ. Do multidisciplinary team meetings make a difference in the management of lung cancer? Cancer 2011 ; 117 : 5112 – 20 . Google Scholar CrossRef Search ADS PubMed 20 Kee F , Owen T , Leathem R. Decision making in a multidisciplinary cancer team: does team discussion result in better quality decisions? Med Decis Making 2004 ; 24 : 602 – 13 . Google Scholar CrossRef Search ADS PubMed 21 Coory M , Gkolia P , Yang IA , Bowman RV , Fong KM. Systematic review of multidisciplinary teams in the management of lung cancer . Lung Cancer 2008 ; 60 : 14 – 21 . Google Scholar CrossRef Search ADS PubMed 22 Oh IJ , Ahn SJ. Multidisciplinary team approach for the management of patients with locally advanced non-small cell lung cancer: searching the evidence to guide the decision . Radiat Oncol J 2017 ; 35 : 16 – 24 . Google Scholar CrossRef Search ADS PubMed © The Author(s) 2017. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/about_us/legal/notices)

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European Journal of Cardio-Thoracic SurgeryOxford University Press

Published: Dec 25, 2017

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