| Literature DB >> 28895087 |
Florian Posch1,2, Richard Partl2,3, Carmen Döller2,3, Jakob M Riedl1,2, Maria Smolle1,2,4, Lukas Leitner2,4, Marko Bergovec2,4, Bernadette Liegl-Atzwanger2,5, Michael Stotz1,2, Angelika Bezan1,2, Armin Gerger1,2, Martin Pichler1,2,6, Karin S Kapp2,3, Herbert Stöger1,2, Andreas Leithner2,4, Joanna Szkandera7,8.
Abstract
BACKGROUND: This study aimed to quantify the benefit of adjuvant radiotherapy (AXRT) for local control, distant metastasis, and long-term survival outcomes in patients with localized soft tissue sarcoma (STS).Entities:
Mesh:
Year: 2017 PMID: 28895087 PMCID: PMC5814515 DOI: 10.1245/s10434-017-6080-3
Source DB: PubMed Journal: Ann Surg Oncol ISSN: 1068-9265 Impact factor: 5.344
Baseline characteristics of the study population (n = 433)
| Variable | Missing dataa
| Overall ( | No AXRT ( | AXRT ( |
|
|
|---|---|---|---|---|---|---|
| Age at entry: years (range) | 433 (0) | 62 [47–73] | 63 [49–75] | 62 [45–73] | 0.26 | 0.82 |
| Female gender | 433 (0) | 212 (49) | 89 (51) | 123 (48) | 0.52 | 0.61 |
| Non-extremity locationd | 433 (0) | 75 (17) | 37 (21) | 38 (15) | 0.08 | 0.48 |
| Deep tumor | 433 (0) | 277 (64) | 108 (62) | 169 (66) | 0.42 | 0.63 |
| Tumor size >5 cm | 433 (0) | 301 (70) | 116 (66) | 185 (72) | 0.23 | 0.41 |
| Resection margin not R0 | 433 (0) | 39 (9) | 26 (15) | 13 (5) | <0.0001 | 0.36 |
| Lymph node metastasis | 426 (2) | 10 (2) | 2 (1) | 8 (3) | 0.18 | 0.86 |
| Distant metastasis | 433 (0) | 0 (0) | 0 (0) | 0 (0) | N/A | N/A |
| Prior unplanned excision (i.e., “whoops procedure”) | 399 (8) | 154 (39) | 48 (31) | 106 (44) | 0.008 | 0.58 |
| Limb salvage | 406 (6) | 377 (93) | 136 (86) | 241 (98) | <0.0001 | 0.49 |
| Histology | 433 (0) | – | – | – | 0.003 | 0.52 |
| Liposarcoma | – | 109 (25) | 62 (35) | 47 (18) | – | – |
| Myxofibrosarcoma | – | 130 (30) | 42 (24) | 88 (34) | – | – |
| Leiomyosarcoma | – | 43 (10) | 16 (9) | 27 (10) | – | – |
| Synovial sarcoma | – | 30 (7) | 9 (5) | 21 (8) | – | – |
| MPNST | – | 13 (3) | 5 (3) | 8 (3) | – | – |
| Other | – | 108 (25) | 41 (23) | 67 (26) | – | – |
| Tumor grade | 433 (0) | – | – | – | <0.0001 | 0.76 |
| G1 | – | 94 (22) | 81 (46) | 13 (5) | – | – |
| G2 | – | 80 (18) | 21 (12) | 59 (23) | – | – |
| G3 | – | 259 (60) | 73 (42) | 186 (72) | – | – |
| AJCC stage 3 | 433 (0) | 165 (38) | 46 (26) | 119 (46) | <0.0001 | 0.82 |
| Postoperative complicationse | 405 (6) | 105 (26) | 33 (21) | 72 (29) | 0.06 | 0.15 |
| (Neo)adjuvant chemotherapy | 433 (0) | 53 (12) | 10 (6) | 43 (17) | 0.001 | 0.86 |
Distribution overall and by adjuvant radiotherapy. Continuous variables are summarized as medians with [25th percentile–75th percentile], whereas categorical variables are reported as absolute frequencies with (percentages)
AXRT adjuvant radiotherapy, N/A not applicable, MPNST malignant peripheral nerve sheath tumor, AJCC American Joint Committee on Cancer
a No. of patients with observed values of the respective variable; % missing in round brackets
b p Values for difference between patients without and with AXRT are from Pearson’s Chi square tests (categorical variables with expected cell counts ≥5), Fisher’s exact tests (categorical variables with expected cell counts <5), or Wilcoxon rank-sum tests (continuous variables)
c p Values correspond to c but are from data after re-weighting with the inverse probability of treatment-weighted (IPTW) analysis
d Non-extremity locations include thoracic/trunk (n = 70) and head/neck (n = 5)
e Postoperative complications include wound healing deficit (n = 41), hematoma (n = 21), infection/abscess (n = 15), (flap) necrosis (n = 7), and others (n = 21)
Outcomes at 5 and 10 years overall and by adjuvant radiotherapy (AXRT) status in unadjusted and inverse probability of treatment-weighted (IPTW) analysis
| End point | Overall cohort ( | No AXRT–unadjusted analysis ( | AXRT–unadjusted analysis ( | No AXRT–IPTW analysis ( | AXRT–IPTW analysis ( |
|---|---|---|---|---|---|
| 5-Year risks | |||||
| Local recurrence | 10 (7–13) | 10 (6–16) | 9 (6–14) | 16 (12–20) | 7 (4–9) |
| Distant metastasis | 19 (15–23) | 17 (11–24) | 20 (15–26) | 24 (20–29) | 18 (15–22) |
| Recurrence-free survival | 64 (58–69) | 66 (58–74) | 62 (55–69) | 56 (N/A) | 66 (N/A) |
| Death from any cause | 26 (22–32) | 24 (17–32) | 28 (22–35) | 33 (N/A) | 24 (N/A) |
| 10-Year risks | |||||
| Local recurrence | 13 (9–17) | 13 (7–20) | 13 (8–19) | 18 (13–22) | 9 (6–12) |
| Distant metastasis | 21 (17–26) | 19 (12–26) | 23 (17–29) | 26 (22–30) | 20 (16–24) |
| Recurrence-free survival | 49 (42–55) | 50 (40–60) | 48 (39–56) | 44 (N/A) | 57 (N/A) |
| Death from any cause | 43 (37–50) | 62 (50–71) | 55 (46–63) | 43 (N/A) | 39 (N/A) |
Local recurrence and distant metastasis were estimated with competing risk analysis, recurrence-free survival with a Kaplan–Meier estimator, and death from any cause with a 1-Kaplan–Meier estimator
CI confidence interval, N/A not applicable (no. of patients in each study group is not meaningful in IPTW; AXRT Adjuvant radiotherapy, 95% CIs could not be estimated for recurrence-free survival and death from any cause in IPTW due to current lack of software implementation (Stata routine “sts generate” currently does not accommodate confidence interval estimation for weighted data)
Fig. 1Cumulative incidence of local recurrence by adjuvant radiotherapy (AXRT) status. a Unadjusted analysis using a competing risk estimator with death from any cause as the competing event. b Inverse probability of treatment-weighted (IPTW) analysis using a competing risk estimator with death from any cause as the competing event
Fig. 2Cumulative incidence of distant metastasis by adjuvant radiotherapy (AXRT) status. a Unadjusted analysis using a competing risk estimator with death from any cause as the competing event. b Inverse probability of treatment-weighted (IPTW) analysis using a competing risk estimator with death from any cause as the competing event
Fig. 3Cumulative incidence of death from any cause by adjuvant radiotherapy (AXRT) status. a Unadjusted analysis using a 1-Kaplan–Meier estimator. b Inverse probability of treatment-weighted (IPTW) analysis using an IPTW-weighted 1-Kaplan–Meier estimator