| Literature DB >> 34907665 |
Yongxing Bao1, Xu Yang1, Yu Men1,2, Jingjing Kang3, Xin Sun1, Maoyuan Zhao1, Shuang Sun1, Meng Yuan1, Zeliang Ma1, Zhouguang Hui1,2.
Abstract
BACKGROUND: For patients with ypN2 non-small cell lung cancer (NSCLC) after neoadjuvant chemotherapy followed by surgery (NCS), the role of postoperative radiotherapy (PORT) is unclear. The aim of our study was to evaluate the effect of PORT on survival of ypN2 NSCLC patients after NCS.Entities:
Keywords: NSCLC; PORT; SEER database; neoadjuvant chemotherapy; ypN2
Mesh:
Year: 2021 PMID: 34907665 PMCID: PMC8807257 DOI: 10.1111/1759-7714.14273
Source DB: PubMed Journal: Thorac Cancer ISSN: 1759-7706 Impact factor: 3.500
FIGURE 1Patient selection
Baseline characteristics of patients with stage ypN2 status NSCLC before and after propensity score matching
| Demographic | Subgroups | Before propensity score matching | After propensity score matching | ||||
|---|---|---|---|---|---|---|---|
| No (%) of patients ( | No (%) of patients ( | ||||||
| Non‐PORT | PORT |
| Non‐PORT | PORT |
| ||
| Age | ≤70 | 95 (76.00%) | 104 (78.79%) | 0.66 | 88 (76.52%) | 91 (79.13%) | 0.75 |
| >70 | 30 (24.00%) | 28 (21.21%) | 27 (23.48%) | 24 (20.87%) | |||
| Year of diagnosis | 2004–2009 | 72 (57.60%) | 55 (41.67%) | 0.01 | 63 (54.78%) | 50 (43.48%) | 0.11 |
| 2010–2015 | 53 (42.40%) | 77 (58.33%) | 52 (45.22%) | 65 (56.52%) | |||
| Race | White | 102 (81.60%) | 105 (79.55%) | 0.86 | 93 (80.87%) | 92 (80.00%) | 0.93 |
| Black | 9 (7.20%) | 9 (6.82%) | 8 (6.96%) | 7 (6.09%) | |||
| Other | 14 (11.20%) | 18 (13.64%) | 14 (12.17%) | 16 (13.91%) | |||
| Gender | Male | 59 (47.20%) | 58 (43.94%) | 0.62 | 55 (47.83%) | 49 (42.61%) | 0.51 |
| Female | 66 (52.80%) | 74 (56.06%) | 60 (52.17%) | 66 (57.39%) | |||
| Histology | Squamous cell carcinoma | 34 (27.20%) | 28 (21.21%) | 0.51 | 29 (25.22%) | 28 (24.35%) | 1.00 |
| Adenocarcinoma | 79 (63.20%) | 89 (67.42%) | 74 (64.35%) | 75 (65.22%) | |||
| Other | 12 (9.60%) | 15 (11.36%) | 12 (10.43%) | 12 (10.43%) | |||
| Differentiation grade | I–II | 48 (38.40%) | 55 (41.67%) | 0.61 | 41 (35.65%) | 44 (38.26%) | 0.79 |
| III–IV | 77 (61.60%) | 77 (58.33%) | 74 (64.35%) | 71 (61.74%) | |||
| Surgery pattern | Lobectomy | 94 (75.20%) | 109 (82.58%) | 0.17 | 90 (78.26%) | 94 (81.74%) | 0.62 |
| Pneumonectomy | 31 (24.80%) | 23 (17.42%) | 25 (21.74%) | 21 (18.26%) | |||
| T stage | T1‐2 | 60 (48.0%) | 78 (59.1%) | 0.07 | 60 (41.2%) | 69 (60.0%) | 0.23 |
| T3‐4 | 65 (52.0%) | 54 (40.9%) | 55 (47.8%) | 46 (40.0%) | |||
| Positive regional nodes | ≤3 | 76 (60.80%) | 57 (43.18%) | 0.01 | 66 (57.39%) | 53 (46.09%) | 0.11 |
| >3 | 49 (39.20%) | 75 (56.82%) | 49 (42.61%) | 62 (53.91%) | |||
FIGURE 2Survival curves according to the use of PORT before and after PSM. (a) OS curves before PSM. (b) OS curves after PSM. (c) CSS curves before PSM. (d) CSS curves after PSM
FIGURE 3Multivariable analysis of predictors for OS and CSS after PSM. (a) Multivariable analysis of predictors for OS. (b) Multivariable analysis of predictors for CSS
FIGURE 4Subgroup analysis of PORT or non‐PORT for OS after PSM
FIGURE 5Subgroup analysis of PORT or non‐PORT for CSS after PSM
Sensitivity analysis for OS and CSS after PSM
| End points | Indicators | Point estimate | Lower 95% CI | Upper 95% CI |
|
|---|---|---|---|---|---|
| OS | Observed HR | 0.59 | 0.43 | 0.82 | 0.001 |
| Calculated RR | 0.70 | 0.56 | 0.87 | ‐ | |
| E value | 2.22 | NA | 1.57 | ‐ | |
| CSS | Observed HR | 0.56 | 0.41 | 0.78 | 0.001 |
| Calculated RR | 0.67 | 0.54 | 0.84 | ‐ | |
| E value | 2.34 | NA | 1.66 | ‐ |