Published OnlineFirst February 5, 2019; DOI: 10.1158/1078-0432.CCR-18-2700
Clinical
Cancer
Research
Translational Cancer Mechanisms and Therapy
Predicting Survival in Patients Undergoing
Resection for Locally Recurrent Retroperitoneal
Sarcoma: A Study and Novel Nomogram from
TARPSWG
Chandrajit P. Raut1, Dario Callegaro2, Rosalba Miceli2, Francesco Barretta2,
Piotr Rutkowski3, Jean-Yves Blay4, Guy Lahat5, Dirk C. Strauss6, Ricardo Gonzalez7,
Nita Ahuja8, Giovanni Grignani9, Vittorio Quagliuolo10, Eberhard Stoeckle11,
Antonino De Paoli12, Venu G. Pillarisetty13, Carolyn Nessim14, Carol J. Swallow15,
Sanjay Bagaria16, Robert Canter17, John Mullen18, Hans J. Gelderblom19,
Elisabetta Pennacchioli20, Frits van Coevorden21, Kenneth Cardona22, Marco Fiore2,
Mark Fairweather1, and Alessandro Gronchi2
Abstract
Purpose: The role of surgery for first relapse locally recurrent
retroperitoneal sarcoma (RPS-LR1) is uncertain. We report
outcomes of the largest RPS-LR1 series and propose a new
prognostic nomogram.
Experimental Design: Patients with consecutive RPS-LR1
without distant metastases who underwent resection at 22
centers (2002–2011) were included. Endpoints were diseasefree and overall survival (DFS, OS) and crude-cumulativeincidence (CCI) of local/distant recurrence from second surgery. Nomograms predicting DFS and OS from second surgery
were developed and validated (calibration plots); discrimination was assessed (Harrell C index).
Results: Of 684 patients identified, full prognostic variable
data were available for 602. Initial surgery for primary RPS was
performed at our institutions in 188 patients (31%) and
elsewhere in 414 (69%). At a median follow-up of 119 months
[Interquartile range (IQR), 80–169] from initial surgery and
Introduction
Surgery is the only potential curative treatment for primary
retroperitoneal sarcoma (RPS). However, the role of surgery for
first relapse locally recurrent RPS (RPS-LR1) is uncertain, as further
recurrence is common. Several studies demonstrated that patients
undergoing surgery for RPS-LR1 have better survival than those
1
Brigham and Women's Hospital, Dana-Farber Cancer Institute, Harvard Medical
School, Boston, Massachusetts. 2Fondazione IRCCS Istituto Nazionale dei
Tumori, Milan, Italy. 3Maria Sklodowska-Curie Memorial Cancer Center, Institute
of Oncology, Warsaw, Poland. 4Centre Leon Berard, Lyon, France. 5Tel Aviv
Sourasky Medical Center, Tel Aviv, Israel. 6Royal Marsden Hospital, London,
United Kingdom. 7Moffitt Cancer Center, Tampa, Florida. 8Johns Hopkins University School of Medicine, Baltimore, Maryland. 9Candiolo Cancer Institute –
FPO, IRCCS, Torino, Italy. 10Istituto Clinico Humanitas IRCCS, Milan, Italy. 11Institut
, Regional Cancer Centre, Bordeaux Cedex, France. 12Centro di RiferBergonie
imento Oncologico, Aviano, Italy. 13Seattle Cancer Care Alliance, University of
Washington School of Medicine, Seattle, Washington. 14The Ottawa Hospital,
University of Ottawa, Ottawa, Canada. 15Mount Sinai Hospital, Princess Margaret
Hospital, University of Toronto, Toronto, Canada. 16Mayo Clinic Jacksonville,
Jacksonville, Florida. 17University of California-Davis School of Medicine, Davis,
75 months (IQR 50–105) from second surgery, 6-year DFS and
OS were 19.2% [95% confidence interval (CI), 16.0–23.0%]
and 54.1% (95% CI, 49.8–58.8%), respectively. Recurrence
patterns and survival probability were histology-specific, with
liposarcoma subtypes having the highest 6-year CCI of second
local recurrence (LR, 60.2%–70.9%) and leiomyosarcoma
(LMS) having higher 6-year CCI of distant metastasis (DM,
36.3%). Nomograms included age at second surgery, multifocality, grade, completeness of second surgery, histology,
chemotherapy/radiotherapy at first surgery, and number of
organs resected at first surgery. OS and DFS nomograms
showed good calibration and discriminative ability (C index
0.70 and 0.67, respectively).
Conclusions: We developed nomograms to predict DFS
and OS for patients undergoing RPS-LR1 resection. Nomograms provide individualized, disease-relevant estimations of
survival for RPS-LR1 patients and assist in clinical decisions.
who do not. However, such studies have inherent selection bias
and cannot predict which subsets of patients may have better
outcomes (1–6).
Nomograms are designed to provide disease-specific, clinically
relevant prognostic models predictive of outcome measures specific to an individual patient. We and others have reported and
California. 18Massachusetts General Hospital, Harvard Medical School, Boston,
Massachusetts. 19Leiden University Medical Center, Leiden, the Netherlands.
20
Istituto Europeo di Oncologia, Milano, Italy. 21Netherlands Cancer Institute,
Amsterdam, the Netherlands. 22Winship Cancer Institute, Emory University
School of Medicine, Atlanta, Georgia.
Note: Supplementary data for this article are available at Clinical Cancer
Research Online (http://clincancerres.aacrjournals.org/).
Corresponding Author: Chandrajit P. Raut, Brigham and Women's Hospital,
Harvard Medical School, Boston, MA 02115. Phone: 617-632-5982; Fax: 617-3943052; E-mail: craut@bwh.harvard.edu
doi: 10.1158/1078-0432.CCR-18-2700
2019 American Association for Cancer Research.
2664 Clin Cancer Res; 25(8) April 15, 2019
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Published OnlineFirst February 5, 2019; DOI: 10.1158/1078-0432.CCR-18-2700
Recurrent Retroperitoneal Sarcoma Nomogram
Translational Relevance
In this, the largest study on first locally recurrent retroperitoneal sarcoma (RPS-LR1), we found that the predominant
pattern of subsequent recurrence was second local recurrence
(LR), though its frequency and its impact on survival were
histology dependent. We developed novel nomograms which,
for the first time, will allow clinicians to provide personalized
prognostic values for disease-free survival (DFS) and overall
survival (OS) to patients undergoing surgery for RPS-LR1 at
dedicated sarcoma centers.
validated single- and multi-institutional nomograms for primary
RPS (2, 7–10). To date, only one single-institution nomogram,
limited to retroperitoneal liposarcoma, included patients with
locally recurrent RPS (2).
The TransAtlantic Retroperitoneal Sarcoma Working Group
(TARPSWG) was established in 2013 as an international collaboration to collectively report outcomes (9, 11–13), propose
treatment guidelines (14, 15), support clinical trials (16), and
develop a prospective registry (RPS Registry, RESAR; ref. 17).
We performed an international study of the largest series
of patients with RPS-LR1 undergoing surgery at TARPSWG
institutions to report outcomes and develop novel nomograms
to estimate disease-free (DFS) and overall survival (OS)
probabilities.
Materials and Methods
Patient cohort
This study was conducted in accordance with recognized ethical
guidelines and was approved by the institutional review boards
(IRB) of each of the contributing centers. Patients on prospective
protocols signed informed consent forms for data collection. Data
on all other patients, including deceased patients, were collected
with IRB approval.
Prospectively or retrospectively collected data on patients with
RPS-LR1 without distant metastases undergoing surgery with
curative intent at 22 dedicated sarcoma centers in eight countries
from January 2002 through December 2011 were collected and
analyzed. "Local recurrence" (LR) was defined as recurrence
within the ipsilateral retroperitoneum, peritoneal cavity, and
pelvis.
Patients who underwent initial surgery for primary RPS at
institutions other than the participating centers were included,
provided surgery for RPS-LR1 was performed at one of our 22
institutions. Patients with concurrent distant metastases were
excluded. "Initial surgery" was defined as curative-intent surgery
for primary RPS. "Second surgery" was defined as curative-intent
surgery for first LR.
Patient and tumor variables, from both operations, included
age, tumor size, grade, histologic subtype, and multifocality.
Tumors were graded according to the Federation Nationale des
Centres de Lutte Contre le Cancer (FNCLCC) grading system (18).
The following histologic subtypes were included: well-differentiated liposarcoma (WDLPS), dedifferentiated liposarcoma
(DDLPS), leiomyosarcoma (LMS), malignant peripheral nerve
sheath tumor (MPNST), solitary fibrous tumor (SFT), and others
(including unclassified/undifferentiated pleomorphic sarcoma).
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Liposarcomas were classified as "well-differentiated" if no dedifferentiated component was present, and as "dedifferentiated" if
such a component was present. Patients with retroperitoneal
presentations of gastrointestinal stromal tumor, desmoid fibromatosis, extraosseous Ewing sarcoma/primitive neuroectodermal
tumor, desmoplastic small round cell tumor, alveolar/embryonal
rhabdomyosarcoma, and uterine sarcoma histologic subtypes
were excluded.
Treatment variables, from both operations, included extent of
resection, number of organs resected, tumor rupture, chemotherapy administration, and radiotherapy administration. Extent of
resection was classified as macroscopically "complete" (R0, negative microscopic margin; or R1, positive microscopic margin) or
macroscopically "incomplete" (R2). Complications were categorized using the Clavien–Dindo classification system (19). Patients
were subsequently followed with clinical examination and surveillance imaging (CT scans of the chest, abdomen, and pelvis)
every 3–4 months for the first 2 years, every 6 months for the
following 3 years, and yearly thereafter. Patients with WDLPS had
less frequent imaging at some institutions (3–6 months during
the first 2–3 years postoperatively) and less routine chest CTs.
Statistical analysis
Patients were classified into two "institution subgroups" based
on whether or not initial surgery for primary RPS was performed at
the participating TARPSWG centers. Association between institution subgroup and patient details, tumor characteristics, and
treatment variables (at both first and second surgery) was studied
in a multivariable logistic model in which the response variable
distinguished the institution subgroup, using the Wald test for
variable testing.
Nomograms were intended to estimate 6-year DFS and OS
probability, measured from date of second surgery. A 6-year
estimate was chosen because median follow-up was 6 years. First
LR, distant metastasis (DM), and death after second surgery were
recorded as events for DFS; concomitant LR and DM were included in computations of DMs. Survival curves were estimated using
the Kaplan–Meier method. The crude cumulative incidence (CCI)
of LR and DM were estimated in a competing risks framework; in
the analysis of LR (DM), deaths without evidence of disease and
DM (LR), whichever occurred first, were regarded as competing
events, and concomitant LRs and DMs were included in the
estimation of the CCI curves for DM.
The putative prognostic variables were the aforementioned
patient details, tumor characteristics, and treatment variables, as
well as disease-free interval (DFI), defined as the time from surgery
for primary RPS to time of first event (date of recurrence). To select
variables for inclusion in multivariable Cox models used to derive
the nomograms, multivariable random forest (RF) models were
used (20). In particular, the relative importance according to the
RF model was determined for each variable, a permutation
procedure was applied to determine the P values associated to
the relative importance (21), and after false discovery rate P value
adjustment (22), the variables significant at 5% were retained. In
the Cox models, the categorical variables were modelled using
dummy variables, and the continuous variables were modelled
using three-knot restricted cubic splines (23). Institution of initial
surgery was modelled as random effect in the multivariable Cox
models and removed when not significant at the likelihood ratio
test. Nomogram performance was assessed by calibration plot
(overall and by cohorts of institution of initial surgery), as an
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Raut et al.
indicator of internal calibration, and the Harrell C statistic, as a
measure of discriminative ability, the latter adjusted for optimism
by applying a bootstrap procedure (24, 25). Data for calibration
plots were stratified into equally sized subgroups, as described
previously (8, 9).
We also evaluated the calibration plots to compare RF predictions and Kaplan–Meier estimates. Moreover, in the multivariable
Cox models, we searched for binary interactions between the
selected covariates, retaining the interactions achieving a P value
<5% after false discovery rate adjustment.
Association between median DFI and selected nomogram
variables was tested in a multivariable quantile regression model,
using the Wald test for variable testing (26).
The statistical analyses were conducted using SAS software (SAS
Institute) and R software (http://www.r-project.org/).
Results
We identified 684 patients who underwent surgery for RPS-LR1
at our 22 TARPSWG institutions (Supplementary Table S1). Full
data on prognostic variables were available for 602 patients
constituting the study cohort (Table 1). Initial surgery for primary
RPS was performed at our 22 institutions in 188 (31.2%) patients
and at the referring center in 414 patients (68.8%). All curativeintent operations for RPS-LR1 were performed at the participating
TARPSWG institutions.
Among patient and tumor characteristics and treatment
variables, only radiation therapy at first surgery (P ¼ 0.003),
number of resected organs at first (P < 0.00001) and second
surgery (P ¼ 0.024), and grade (P ¼ 0.029) were significantly
associated with institution type of first surgery (TARPSWG vs.
elsewhere). In particular, patients undergoing initial surgery at
TARPSWG centers more commonly received radiotherapy at
first surgery, had more organs resected at first surgery and fewer
at second surgery, and had a higher frequency of grade 3 tumors
(data not shown).
Oncologic outcomes
Median DFI from initial surgery to RPS-LR1 was 19 months
[Interquartile range (IQR), 6–41]. Median follow-up was 119
months (IQR, 80–169) from primary RPS surgery and 75
months (IQR 50–105) from definitive surgery for RPS-LR1.
Clavien–Dindo grade 3 or higher complications were observed
after second surgery in 103 (17.1%) patients, and 67 (11.1%)
required reoperations for complications. There were five postoperative deaths (0.8%) at 1, 3, 38, 47, and 68 days from
second surgery (four treatment-related, one due to a perioperative cardiac event).
Median DFI after second surgery was 19 months (IQR, 8–57).
The most common pattern of disease was a second LR (58.2%).
Number of first and overall events and 6-year CCI for second LR,
distant metastases, and death after second surgery are included in
Supplementary Table S2 and Fig. 1A. Distant metastases as a first
event were rarely detected beyond two years following second
surgery, whereas risk of second LR continued progressively
(Fig. 1A). Of note, 41 patients died as first event after second
surgery, without documented recurrence (unknown causes).
Excluding 5 patients who died of postoperative complications,
median time to death was 12 months (IQR, 6–20). CCI probabilities of LR and DM by histology demonstrated that second
recurrences for WDLPS/DDLPS subtypes were most commonly
2666 Clin Cancer Res; 25(8) April 15, 2019
Table 1. Cohort characteristics
First surgery
Gender
Female
Male
Age
Tumor size, median (IQR)
FNCLCC grade
1
2
3
Histologic subtype
DD LPS
WD LPS
LMS
SFT
MPNST
Other
Completeness of resection
R0/R1
R2
Not available
Number of resected organs
Median (IQR)
0
1
>1
Tumor rupture
No
Yes
Not available
Multifocality
No
Yes
Not available
Chemotherapy
Given
Preop, postop, pre- and
postop, unknown
Given at either first and/or
second surgery
Not given
Radiotherapy
Given
Preop, intraop, postop, preand postop, unknown
Given at either first and/or
second surgery
Not given
DFI after first surgery,
median (IQR)
N ¼ 602 (%)
Second surgery
311 (51.7)
291 (48.3)
56.0 yrs (47.0–64.0)
59.0 yrs (50.0–67.8)
18.0 cm (12.0–26.0)
11.0 cm (6.3–18.0)
195 (32.4)
170 (28.2)
237 (39.4)
266 (44.2)
169 (28.1)
73 (12.1)
14 (2.3)
7 (1.2)
73 (12.1)
398 (66.1)
118 (19.6)
86 (14.3)
517 (85.9)
85 (14.1)
0
1 (0–2)
265 (44.0)
146 (24.3)
191 (31.7)
2 (1–3)
127 (21.1)
151 (25.1)
324 (53.8)
363 (60.3)
77 (12.8)
162 (26.9)
521 (86.5)
67 (11.1)
14 (2.3)
399 (66.3)
57 (9.5)
146 (24.2)
378 (62.8)
224 (37.2)
0
87 (14.5)
167 (27.7)
18 (3.0), 64 (10.6),
109 (18.1), 42 (7.0),
5 (0.8), 0 (0)
14 (2.3), 2 (0.3)
226 (37.5)
515 (85.5)
435 (72.3)
75 (12.5)
18 (3.0), 3 (0.5),
52 (8.6), 2 (0.3), 0
185 (30.7)
85 (14.1), 27 (4.5),
66 (11.0), 4 (0.7),
3 (0.5)
168 (27.9)
527 (87.5)
417 (69.3)
19.0 months (6.3–41.0)
local and for LMS were most commonly distant metastases
(Table 2; Fig. 1B and C).
Three- and 6-year DFS from second surgery were 32.6% (95%
CI, 29.0%–36.7%) and 19.2% (95% CI, 16.0%–23.0%), respectively (Fig. 2A). Three- and 6-year OS were 70.2% (95% CI,
66.4%–74.1%) and 54.1% (95% CI, 49.8%–58.8%), respectively
(Fig. 2A). When stratified by histology, patients with WDLPS had
the most favorable DFS and OS, whereas patients with grade 3
DDLPS generally had the worst (Fig. 2B and C).
Nomogram development
RF significant predictors included in the DFS and OS nomograms were: multifocality (second surgery), grade, completeness
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Recurrent Retroperitoneal Sarcoma Nomogram
Figure 1.
CCI curves of LR and DM as first events after second surgery (A), of LR by histology (B), of DM by histology (C).
of second surgery, histology, and radiotherapy (first surgery;
Supplementary Table S3). Chemotherapy at first surgery was
independently predictive of DFS, whereas age at second surgery
was significant for OS. The number of organs resected at first
surgery was significant in the RF DFS model (P ¼ 0.033) and, even
though it achieved a P value of 0.095 in the OS model, we
included it as a predictive variable in the OS nomogram for the
reasons below. The variables above were included in multivariable Cox models used to develop the nomogram (Table 3).
Institution type (TARPSWG vs. elsewhere) was initially modelled
as random effect but was removed, as it was not statistically
significant (P ¼ 0.462 for DFS, P ¼ 0.950 for OS).
If we removed three of the four selected variables significantly
associated with the institution type (i.e. radiotherapy at first
surgery, number of resected organs at first surgery, and grade)
from the Cox models, then institution of initial surgery reached
statistical significance (P ¼ 0.003 for DFS, 0.038 for OS). This could
mean that such variables had succeeded in modeling the institution heterogeneity, thus reinforcing our idea of keeping number of
resected organs in the OS nomogram. DFI was excluded because of
its strong association with other nomogram-selected variables,
such as age at second surgery (P ¼ 0.003), number of organs
resected at first surgery (P ¼ 0.037), grade (P ¼ 0.0003), histology
(P ¼ 0.033), and radiotherapy (P ¼ 0.0004) or chemotherapy at
Table 2. Histology-specific patterns of recurrence and survival
Histology
WDLPS (N ¼ 169)
DDLPS, grade 1–2 (N ¼ 137)
DDLPS, grade 3 (N ¼ 129)
LMS (N ¼ 73)
MPNST (N ¼ 7)
SFT (N ¼ 14)
Other (N ¼ 73)
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% 6-Year CCI,
LR (95% CI)
60.2 (52.4–69.0)
61.0 (52.9–70.2)
70.9 (62.9–79.8)
44.0 (33.3–58.2)
28.6 (7.8–100.0)
71.4 (48.9–100.0)
45.9 (35.0–60.3)
% 6-Year CCI,
DM (95% CI)
4.6 (2.2–9.5)
9.7 (5.8–16.2)
13.6 (8.4–22.0)
36.3 (26.2–50.1)
50.0 (17.8–100.0)
21.4 (7.1–64.6)
24.2 (15.9–36.8)
% 6-Year DFS
(95% CI)
30.3 (23.4–39.1)
22.6 (16.2–31.3)
6.5 (3.0–14.5)
12.4 (6.4–24.2)
21.4 (4.2–100.0)
7.1 (10.8–47.2)
17.7 (10.0–31.2)
% 6-Year OS
(95% CI)
77.1 (70.1–84.7)
54.6 (46.3–64.6)
32.2 (23.9–43.5)
45.4 (33.8–60.8)
35.7 (8.3–100.0)
56.2 (35.2–90.0)
48.3 (37.1–62.8)
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Figure 2.
Kaplan–Meier curves of DFS and OS after second surgery (A), of DFS by histology (B), of OS by histology (C).
first surgery (P ¼ 0.029), from the multivariable quantile regression model. In particular, high median DFI corresponded to older
age, higher number of resected organs, low grade, SFT or other
histology, and radiotherapy or chemotherapy administration.
The nomograms to predict 6-year DFS and OS for patients
undergoing curative-intent surgery for RPS-LR1 are shown
in Fig. 3A and B and their scoring system are presented in
Supplementary Table S4 and S5. At internal validation, both
nomograms showed good calibration (Supplementary Fig.
S1A– S1F), independently from the sets used for validation
(patients undergoing initial surgery at TARPSWG institutions and
patients undergoing surgery elsewhere). The discriminative ability, according to the Harrell C index, was 0.70 for OS nomogram
and 0.67 for DFS nomogram.
Table 3. Multivariable analysis
Factor
Resected number of organs at first surgery
Age at second surgery
Multifocality at second surgery, yes vs. no
Grade – 3 vs. 1–2
Completeness of surgery at second surgery, incomplete vs. complete
Histology
LMS vs. DDLPS
WDLPS vs. DDLPS
MPNST vs. DDLPS
Other vs. DDLPS
SFT vs. DDLPS
Chemotherapy administered at first surgery, yes vs. no
Radiotherapy administered at first surgery, yes vs. no
2668 Clin Cancer Res; 25(8) April 15, 2019
DFS After second surgery
HR (95% CI)
P
1.31 (1.04–1.63)
0.001
—
—
1.87 (1.54–2.27)
<0.001
1.51 (1.21–1.87)
<0.001
1.65 (1.27–2.15)
<0.001
0.013
1.14 (0.85–1.54)
0.66 (0.51–0.85)
1.53 (0.62–3.77)
1.11 (0.82–1.50)
0.94 (0.54–1.66)
1.22 (0.93–1.61)
0.145
1.06 (0.80–1.41)
0.679
OS After second surgery
HR (95% CI)
P
1.57 (1.17–2.11)
0.002
1.33 (1.10–1.59)
0.005
1.78 (1.39–2.28)
<0.001
1.82 (1.37–2.40)
<0.001
2.14 (1.55–2.96)
<0.001
0.001
0.79 (0.54–1.15)
0.46 (0.32–0.66)
1.21 (0.37–3.98)
1.02 (0.70–1.49)
0.51 (0.24–1.11)
—
—
1.15 (0.82–1.62)
0.407
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Recurrent Retroperitoneal Sarcoma Nomogram
Figure 3.
Nomograms to predict 6-year DFS (A) and OS (B) after second surgery in patients with recurrent RPS . Instructions: each nomogram provides a method of
calculating the 6-year DFS or OS probability on the basis of a patient's combination of covariates. For instance, in the DFS nomogram, locate the patient-specific
multifocality at second surgery, draw a line straight up to the "Points" axis to determine the associated score. Repeat for the other nomogram variables, sum the
scores, and locate the total score on the "Total Points" axis. Draw a line straight down to the "6-year DFS Probability" axis to obtain the probability.
Discussion
Management of patients with first locally recurrent RPS is a
challenging conundrum encountered frequently in high-volume sarcoma centers. There are no evidence-based guidelines
drawn from any large studies to guide the clinicians. This is the
largest study to report outcomes, and the first to propose new
nomograms predictive of DFS and OS for patients undergoing
curative-intent second surgery for RPS-LR1. These nomograms
provide individualized and disease-relevant estimation of DFS
and OS and will assist in clinical decision-making. Both
nomograms were internally validated and perform well for
patients irrespective of the site of initial surgery for primary
RPS. Thus, they can be implemented in real-world clinical
encounters.
The strengths of our study are its size (602 patients), breadth
(22 centers), scope (all common RPS histologies), and focus (only
RPS-LR1). Only one prior study, limited to patients with RP LPS,
proposed a nomogram which incorporated both patients with
primary and locally recurrent RPS (2). Interestingly, recurrent RPS
was significant on univariate but not multivariate analysis in that
study, likely due to other relevant confounding variables (multifocality, histology). Nevertheless, it remained in the model, given
other studies reporting its significance and improved calibration
accuracy without affecting concordance. However, that nomogram included only 102 patients with recurrent disease and was
not designed to distinguish prognostic factors within a cohort of
patients with recurrent RPS.
Several points from our study warrant further comment. First,
we found that higher number of organs resected at initial surgery
was a negative prognostic factor for both DFS and OS after second
surgery. This should not be interpreted as endorsing a less aggressive resection at initial presentation simply to increase the probability of improving DFS and OS at recurrence. Rather, this more
likely suggests that patients who undergo an extensive multivisceral resection initially and subsequently recur have aggressive
tumor biology, whereas those who undergo an initial simple
excision and recur may still have disease that can be salvaged by a
more extended procedure. Essentially, it is an indirect measure of
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the ability for surgical salvage at first recurrence, predicated on the
extent of initial treatment and tumor biology.
Second, DFI was not selected as a predictive variable in either
nomogram. This may be a composite variable, because some
patients identified early as locally recurrent may in fact have had
low-volume persistent disease (such as indolent WDLPS in perinephric fat), whereas others truly had rapid recurrence with worse
outcome. This may explain DFI's strong association with many
nomogram variables (number of organs resected, grade, histology, etc.), which led to its exclusion from the nomogram variables
set.
Third, grade 3 DDLPS was the histologic subtype associated
with the worst DFS and OS outcomes. Compared with primary
grade 3 DDLPS, which may both recur locally and spread systemically, patients with first locally recurrent grade 3 retroperitoneal DDLPS amenable to a second surgical procedure tend to
recur again locally. Their metastatic risk is comparatively low.
Moreover, although DFS of grade 3 DDLPS and LMS was similar
and poor, OS of LMS was better, which may be related to the
broader armamentarium of systemic agents for LMS (27). Of note,
chemotherapy and radiotherapy administration at second surgery
were removed from the model, as both appeared to represent
selection bias.
Fourth, treatment practices for patients with primary RPS and
recurrent sarcoma have changed over the period of this study and
may vary between centers, including extent of surgery, chemotherapy regimens, and radiation delivery. No differences were
noted between TARPSWG centers in terms of number of organs
resected at second surgery and use of chemotherapy or radiation.
Although more contemporary chemotherapy regimens improve
survival in patients with metastatic disease, their impact in this
study population is uncertain, and thus, our data are valid
irrespective of treatment era.
Fifth, the fact that site of initial surgery for primary RPS has no
impact on outcome after second surgery (for RPS-LR1) may be
surprising. It suggests that salvage surgery for first recurrence may
balance out the inadequacy of first surgery. This may be due to
more aggressive second surgery. Of 414 patients undergoing first
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Raut et al.
surgery elsewhere, 225 (54.3%) had multivisceral resections at
second surgery. In contrast, only 75 of 188 (38.3%) patients
undergoing both operations at our institutions underwent multivisceral resection at second surgery. We previously demonstrated
that surgery for primary RPS performed at high-volume sarcoma
centers was associated with improved OS (11). There is an
inherent selection bias given that we selected for patients who
were candidates for surgery, so we lack data on those who
underwent first surgery elsewhere and were not candidates for
second surgery upon recurrence. Therefore, we still stress that
initial surgery at dedicated sarcoma centers is associated with
better outcomes when measured from initial treatment. Nonetheless, this study suggests that for patients undergoing initial
surgery at a nonspecialized center who develop resectable RPSLR1 and who are both candidates for and undergo second surgery
at a dedicated sarcoma center, DFS and OS may still match that of
patients undergoing both the initial and second surgery at the
dedicated sarcoma centers.
Finally, our choice to derive the nomograms from multivariable Cox models instead of directly using the RF models predictions may be criticized. Predicted probabilities may be obtained
directly with a RF model (accommodating complex interactions
between the covariates), which can be interpreted as an advantage.
However, this was not the case with our data. The calibration was
only slightly improved when using RF models (e.g., the calibration plot for RF DFS probabilities in Supplementary Fig. S2, to be
compared with the calibration plot for Cox model DFS probabilities in Fig. 1A; the RF model overestimated the observed DFS in
the third subgroup and underestimated DFS in the seventh
subgroup). Instead, we tried to incorporate the covariate interactions in the Cox models; the models including the significant
interactions (see statistical analysis section) gave a slight calibration improvement (Supplementary Fig. S3 for the DFS model)
against the increase of model degrees of freedom (17 additional
interaction terms for the DFS model), with consequent overfitting
problems.
Few studies have reported prognostic factors in patients with
locally recurrent RPS undergoing surgery. Several reported that
patients with RPS-LR1 undergoing surgery had better survival than
those that did not (1, 3, 4, 28). Gyorki and Brennan identified
resectability of LR as the most significant predictor of outcome (4).
Grobmeyer and colleagues identified high grade and no resection
as negative prognostic factors (28). Ikoma and colleagues found
that patients with recurrent retroperitoneal LMS, who underwent
salvage surgery, had better OS than those who did not, regardless of
whether the recurrence was local or distant (3). Park and colleagues
reported that patients with locally recurrent retroperitoneal LPS
with growth rates of less than 9 mm per month, who underwent
resection, had better disease-specific survival than those with the
same growth rate that did not undergo resection or with a faster
growth rate regardless of whether surgery was performed (6). Yang
and colleagues identified additional factors, such as higher histologic grade and DFI of less than 1 year, as poor prognostic factors
among 50 patients with RPS-LR1 undergoing surgery (29). Likewise, a previous study by Gronchi and colleagues on a series of 377
patients undergoing surgery showed that WDLPS histology subtype and DFI were independent predictor of postrelapse outcome (21). These studies generally reflect selection bias favoring
patients undergoing surgery who may have lower volume disease,
less vascular involvement, longer DFIs, more favorable histologies,
and other favorable markers of tumor biology.
2670 Clin Cancer Res; 25(8) April 15, 2019
Importantly, our data do not justify surgery in all patients with
RPS-LR1. In fact, in our previously reported experience, 52% of
patients with RPS-LR1 did not undergo surgery. Our new nomograms can help identify patients, amongst a cohort of those with
resectable recurrences, who potentially have more favorable
outcomes.
There are several limitations to our study. First, because these
data were analyzed retrospectively (though some of the databases
were maintained prospectively), we did not collect data on
indications for surgery, such as symptoms, which could skew the
outcomes. We are currently conducting a prospective primary
RESAR, which will further characterize indications for surgery (17). Second, pathology was not reviewed centrally. Therefore, there may be some discrepancy amongst pathologists about
issues such as FNCLCC grade in DDLPS. Third, this nomogram is
not applicable to all patients with locally recurrent or metastatic
RPS or with second or later recurrences. It is based on and designed
for patients undergoing surgery for RPS-LR1 disease. Fourth, just
as there is a selection bias in studies reporting that patients with
RPS-LR1 disease undergoing surgery have better outcomes than
those that do not, our study also has an inherent selection bias. All
patients underwent second surgery at TARPSWG institutions, and
thus, it is possible that our nomograms provide at best an upper
limit on potential outcomes of individuals with RPS-LR1 undergoing surgery. Nevertheless, the nomograms will help clinicians
predict survival outcomes in patients considered operable, but
cannot compare outcomes with and without surgery for individual patients. Finally, although most contemporary sarcoma studies focus on histology (usually nonretroperitoneal sites), we still
included all histologies in the retroperitoneum, albeit modeled
separately and accounted for in the model. The rarity of RPS has,
to date, limited our ability to parse data about the different RPS
histologies. However, our TARPSWG collective now has datasets
that can help future studies focus on individual RPS histologies.
These nomograms were constructed from a large group of
institutions, and as such, they are broadly applicable. The nomograms have been added to the "Sarculator" app (http://www.
sarculator.com) for mobile devices and are being used by the
authors in patient consultations.
In conclusion, we found that the predominant pattern of
subsequent recurrence was second LR, though this was histology dependent. Similarly, DFS and OS were histology dependent. New nomograms will, for the first time, allow clinicians to
provide personalized prognostic values for DFS and OS to
patients undergoing surgery for RPS-LR1 disease at dedicated
sarcoma centers.
Disclosure of Potential Conflicts of Interest
D. Callegaro reports receiving speakers bureau honoraria from Eli Lilly and
Company. P. Rutkowski reports receiving speakers bureau honoraria from
Novartis, Bristol-Myers Squibb, Pfizer, and Eli Lilly, and is a consultant/advisory
board member for Novartis, MSD, Blueprint Medicines, Bristol-Myers Squibb,
and Roche. N. Ahuja reports receiving commercial research grants from Astex
and Cepheid, and holds ownership interest (including patents) in IBM. G.
Grignani is a consultant/advisory board member for Pharmamar, Lilly, Novartis, and EISAI. No potential conflicts of interest were disclosed by the other
authors.
Authors' Contributions
Conception and design: C.P. Raut, D. Callegaro, R. Miceli, P. Rutkowski,
G. Lahat, D.C. Strauss, R. Gonzalez, N. Ahuja, V.G. Pillarisetty, C. Nessim,
C.J. Swallow, R. Canter, J. Mullen, E. Pennacchioli, M. Fiore, A. Gronchi
Clinical Cancer Research
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Published OnlineFirst February 5, 2019; DOI: 10.1158/1078-0432.CCR-18-2700
Recurrent Retroperitoneal Sarcoma Nomogram
Development of methodology: C.P. Raut, D. Callegaro, R. Miceli, D.C. Strauss,
R. Gonzalez, E. Stoeckle, C. Nessim, C.J. Swallow, R. Canter, K. Cardona
Acquisition of data (provided animals, acquired and managed patients,
provided facilities, etc.): C.P. Raut, D. Callegaro, P. Rutkowski, J.-Y. Blay,
G. Lahat, D.C. Strauss, R. Gonzalez, N. Ahuja, G. Grignani, E. Stoeckle, A. De
Paoli, V.G. Pillarisetty, C. Nessim, C.J. Swallow, S. Bagaria, R. Canter, J. Mullen,
H.J. Gelderblom, E. Pennacchioli, F. van Coevorden, K. Cardona, M. Fiore,
M. Fairweather, A. Gronchi
Analysis and interpretation of data (e.g., statistical analysis, biostatistics,
computational analysis): C.P. Raut, D. Callegaro, R. Miceli, F. Barretta,
J.-Y. Blay, D.C. Strauss, R. Gonzalez, G. Grignani, S. Bagaria, J. Mullen, F. van
Coevorden, M. Fairweather, A. Gronchi
Writing, review, and/or revision of the manuscript: C.P. Raut, D. Callegaro,
R. Miceli, F. Barretta, P. Rutkowski, J.-Y. Blay, D.C. Strauss, R. Gonzalez,
N. Ahuja, G. Grignani, E. Stoeckle, A. De Paoli, V.G. Pillarisetty, C. Nessim,
R. Canter, J. Mullen, H.J. Gelderblom, E. Pennacchioli, F. van Coevorden,
K. Cardona, M. Fiore, M. Fairweather, A. Gronchi
Administrative, technical, or material support (i.e., reporting or organizing
data, constructing databases): C.P. Raut, D. Callegaro, D.C. Strauss,
V. Quagliuolo, M. Fairweather
Study supervision: C.P. Raut, D. Callegaro, D.C. Strauss, A. Gronchi
The costs of publication of this article were defrayed in part by the
payment of page charges. This article must therefore be hereby marked
advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate
this fact.
Received August 22, 2018; revised November 21, 2018; accepted
January 24, 2019; published first February 5, 2019.
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Predicting Survival in Patients Undergoing Resection for Locally
Recurrent Retroperitoneal Sarcoma: A Study and Novel Nomogram
from TARPSWG
Chandrajit P. Raut, Dario Callegaro, Rosalba Miceli, et al.
Clin Cancer Res 2019;25:2664-2671. Published OnlineFirst February 5, 2019.
Updated version
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