ABSTRACT
Background
Advanced sarcomas have limited treatment options. Gemcitabine and docetaxel (GD) regimen showed efficacy in soft tissue sarcomas (STSs) in phase II studies but failed in first‐line phase III trial. Adding cisplatin to GD showed efficacy in other types of cancer. mTOR pathway has been shown to play a role in resistance to these drugs. Inflammatory biomarkers have been identified as potential prognostic indicators in various malignancies, but their role in patients with advanced sarcomas is not clear.
Methods
We retrospectively enrolled 77 patients with advanced or metastatic sarcomas (STSs, n = 71; bone sarcomas, n = 6) receiving a novel combination with gemcitabine‐gemcitabine/docetaxel/cisplatin plus everolimus (G‐GDC + E). Primary endpoints included overall survival (OS) and progression‐free survival (PFS). Inflammatory biomarkers were calculated, and their prognostic influence was evaluated.
Results
The median OS and PFS were 16.8 months (95% CI, 13.6–23.9) and 5.4 months (95% CI, 4.3–8.3), respectively. Undifferentiated pleomorphic sarcoma/myxofibrosarcoma (UPS/MFS) demonstrated superior PFS compared to round cell sarcoma/translocation‐related sarcoma (7.8 vs. 3.6 months, p = 0.009) and bone sarcoma (7.8 vs. 2.3 months, p < 0.001). Eastern Cooperative Oncology Group Performance Status ≥ 2, unfavorable histology (round cell sarcoma/translocation‐related sarcoma and bone sarcoma), lower albumin level, and lymphocyte‐to‐monocyte ratio < 2.7 were independent predictors of OS. Grade 3–4 toxicities included neutropenia (68.8%), thrombocytopenia (59.7%), anemia (49.4%), diarrhea (18.2%), and skin toxicities (28.6%).
Conclusions
G‐GDC + E demonstrates histology‐specific efficacy in advanced/metastatic sarcomas, with substantial hematologic toxicity (Grade 3–4 thrombocytopenia 59.7%, neutropenia 68.8%) and notable non‐hematologic events (Grade 3–4 diarrhea 18.2%, skin reactions 28.6%), all controllable with close monitoring, dose modifications and supportive care. Inflammatory biomarkers provide independent prognostic values.
Keywords: cisplatin, docetaxel, everolimus, gemcitabine, sarcoma, systemic inflammation biomarkers
Late‐line gemcitabine, docetaxel, cisplatin, and everolimus yield a 45.5% objective response rate and prolonged survival in selected advanced sarcoma subtypes. Prognostic stratification was enhanced by ECOG performance status and lymphocyte‐to‐monocyte ratio, highlighting their potential role in treatment individualization.
1. Introduction
Sarcomas are tumors from mesenchymal tissues, diverse in location, histology, molecular profile, and prognosis, making up about 1% of adult cancers [1, 2]. For localized extremity disease, wide excision with adjuvant therapies can achieve a 5‐year metastasis‐free survival rate around 60%–70% [3, 4, 5]. However, for retroperitoneal sarcoma, achieving complete surgical resection with negative margins is difficult, and local recurrence often leads to treatment failure [6].
Chemotherapy continues to be the primary approach for treating advanced or metastatic soft tissue sarcomas (STSs). Standard first‐line therapy consists of single‐agent anthracycline; however, combining anthracyclines with other agents may enhance progression‐free survival (PFS) and response rates but not overall survival (OS), albeit at the cost of increased toxicity [7, 8, 9]. One essential exception is the trabectedin‐doxorubicin combination, which has demonstrated improved OS for patients with leiomyosarcoma (LMS) compared to adriamycin monotherapy [10].
The combination of gemcitabine and docetaxel (GD) is a non‐anthracycline regimen used in the treatment of STSs. A previous study indicated that extending gemcitabine infusion to 90 min increases the duration of elevated plasma concentrations and intracellular accumulation of gemcitabine triphosphate [11]. Additionally, administering gemcitabine followed by docetaxel shows a synergistic effect, whereas the reverse sequence is antagonistic [12]. These findings established the current GD dosing schedule. Although efficacy has been demonstrated in multiple phase II studies [13, 14], GD did not show superiority over adriamycin in a phase III trial for first‐line advanced STS treatment [15]. The GD combination has also demonstrated activity in bone sarcoma (BS). The SARC 003 phase II trial evaluated GD across multiple sarcoma subtypes including osteosarcoma (OGS), Ewing sarcoma, and chondrosarcoma, though the response rate was modest [16]. A systematic review demonstrated an overall response rate (ORR) of 10.7% with a disease control rate (DCR) of 35% across 197 OGS patients treated with GD [17]. Nevertheless, the GD combination remains a commonly used regimen in subsequent lines of therapy for advanced or metastatic disease among various available options [18, 19, 20, 21]. Thus, improving GD's effectiveness warrants further investigation.
One strategy to improve GD efficacy is to combine with other chemotherapeutic agents. Combination of gemcitabine‐carboplatin‐docetaxel was found to achieve a high response rate in urothelial carcinoma (UC) [22], especially in sarcomatoid variant [23]. Similar findings were noted in non‐small cell lung cancer (NSCLC) [24, 25]. Another strategy is to target the drug resistance mechanism. Mammalian target of rapamycin (mTOR) pathway has been shown to be responsible for the resistance to gemcitabine [26, 27], docetaxel [28, 29], and cisplatin [30]. In addition, everolimus, an oral mTOR inhibitor, and other mTOR inhibitors also showed modest anti‐cancer activity in STS [31, 32]. The PI3K/mTOR pathway represents a therapeutic vulnerability across multiple BS subtypes, with preclinical evidence of mTOR inhibitor activity in both OGS [33, 34] and chondrosarcoma [35]. Cisplatin‐based regimens remain an essential component of OGS treatment [36]. Therefore, incorporating everolimus and platinum into the GD regimen may offer a promising therapeutic combination in sarcoma.
Recent studies have shown that tumor microenvironment (TME) has an impact on prognosis and treatment response of cancer [37, 38, 39], including sarcoma [40, 41]. However, it is not possible to assess complex TME in a routine clinical setting. On the other hand, inflammatory biomarkers obtained through simple blood testing, including neutrophil‐to‐lymphocyte ratio (NLR), platelet‐to‐lymphocyte ratio (PLR), lymphocyte‐to‐monocyte ratio (LMR), and C‐reactive protein‐to‐albumin ratio (CAR), have emerged as potential surrogate markers for TME across various non‐sarcoma [42, 43, 44, 45, 46, 47] as well as sarcoma malignancies [48, 49]. Therefore, the prognostic relevance of these markers in advanced STS patients undergoing a unique late‐line combination chemotherapy deserves further investigation.
This retrospective study aimed to evaluate the efficacy and safety of a novel combination therapy, gemcitabine‐gemcitabine/docetaxel/cisplatin plus everolimus (G‐GDC + E), in patients with advanced or metastatic sarcomas. Additionally, the study sought to identify potential prognostic factors associated with survival outcomes by analyzing various clinical, pathological, and inflammatory parameters.
2. Patients and Methods
2.1. Treatment Protocol, Study Design, and Patient Selection
This retrospective cohort study assessed patients with pathologically confirmed advanced or metastatic sarcomas treated with the G‐GDC + E regimen at our institute from January 1, 2010, to December 31, 2024. The G‐GDC + E regimen included everolimus 10 mg orally on Days 1, 8, and 15; gemcitabine 800 mg/m2 intravenously for 80 min on Day 1; and gemcitabine, docetaxel, and cisplatin given on Day 8 under the following sequence: gemcitabine 800 mg/m2 for 80 min, followed by docetaxel 60 mg/m2 intravenously for 120 min, then cisplatin 60 mg/m2 intravenously for 180 min, repeated every 28 days. This administration sequence was maintained consistently across all patients to exploit sequence‐dependent cytotoxic synergy.
Treatment continued until disease progression, unacceptable toxicity, or patient withdrawal. Dose modifications follow standard guidelines based on toxicity. Prophylactic granulocyte colony‐stimulating factor was used per institutional protocols for patients with high‐risk factors for febrile neutropenia or those who experience severe neutropenia in previous cycles. The study protocol was approved by the Institutional Review Board of Taipei Veterans General Hospital (Approval Number: 2024‐10‐002ACF).
2.2. Data Collection and Assessment Parameters
Demographic, clinical, and laboratory data were extracted from electronic medical records. Information collection included age, gender, anthropometric measurements (body height, body weight, body mass index), Eastern Cooperative Oncology Group performance status (ECOG PS), and comorbidities (including type 2 diabetes mellitus (T2DM), hypertension (HTN), dyslipidemia, and fatty liver disease). Primary tumor histology, locations, and metastatic status were documented. Missing data was minimal (< 5% for all variables) and handled by complete case analysis.
Blood‐based inflammatory biomarkers were calculated as follows: neutrophil‐to‐lymphocyte ratio (NLR = absolute neutrophil count/absolute lymphocyte count) [50]; platelet‐to‐lymphocyte ratio (PLR = platelet count/absolute lymphocyte count) [45, 51]; lymphocyte‐to‐monocyte ratio (LMR = absolute lymphocyte count/absolute monocyte count) [42, 52]; systemic immune‐inflammation index (SII = platelet count × neutrophil count/lymphocyte count) [43]; c‐reactive protein‐to‐albumin ratio (CAR = C‐reactive protein/albumin) [44].
Treatment‐related adverse events (AEs) were assessed according to the National Cancer Institute Common Terminology Criteria for Adverse Events (CTCAE) version 5.0 [53].
2.3. Outcome Measures
The primary endpoints were OS, defined as the time from treatment initiation to death from any cause, and PFS, defined as the time from treatment initiation to disease progression or death, whichever occurred first. Tumor response was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1 [54]. Secondary endpoints include objective response rate (ORR), defined as the proportion of patients achieving complete response (CR) or partial response (PR), and disease control rate (DCR), defined as the proportion of patients achieving CR, PR, or stable disease (SD).
2.4. Statistical Analysis
To identify optimal cut‐off values for inflammatory biomarkers (NLR, PLR, LMR, SII, and CAR), we performed receiver operating characteristic (ROC) curve analysis with Youden's index, using 1‐year OS as the binary outcome. Survival analyses were performed using the Kaplan–Meier (K‐M) method, with differences between groups assessed using the log‐rank test.
Univariate and multivariate Cox proportional hazards regression models were used to identify factors associated with OS and PFS. Variables with p‐values < 0.1 in univariate analyses were included in the multivariate model using a backward stepwise selection procedure. A post hoc power analysis was conducted to ensure the adequacy of the sample size for detecting clinically meaningful differences in survival outcomes. Histologic subtype analyses were performed using pairwise comparisons between two subtypes at a time (Tables S1 and S2).
All statistical analyses were performed using R software version 4.1.0 (R Foundation for Statistical Computing, Vienna, Austria). A two‐sided p‐value < 0.05 was considered statistically significant.
3. Results
3.1. Patient Characteristics
Among 106 initially identified patients, 77 met the inclusion criteria after excluding those with uncertain diagnosis (n = 2), declining treatment (n = 2), receiving concurrent pembrolizumab (n = 2), and receiving less than one complete treatment cycle (n = 23). The baseline characteristics are summarized in Table 1. The median age was 51.8 years (IQR, 43.1–57.9), with 53.2% male patients. Most patients (84.4%) had ECOG PS 0–1.
TABLE 1.
Baseline characteristics of patients with sarcoma (N = 77).
| Characteristics | Value |
|---|---|
| Demographics | |
| Age, years, median (IQR) | 51.8 (43.1–57.9) |
| Male sex, n (%) | 41 (53.2) |
| Anthropometric and nutritional parameters | |
| Body weight, kg, mean (95% CI) | 65.6 (62.1–69.0) |
| Body mass index, kg/m2, mean (95% CI) | 24.0 (22.7–25.3) |
| Performance status, ECOG, n (%) | |
| 0 | 24 (31.2) |
| 1 | 41 (53.2) |
| 2 | 12 (15.6) |
| Comorbidities, n (%) | |
| Type 2 diabetes mellitus | 11 (14.3) |
| Hypertension | 24 (31.2) |
| Dyslipidemia | 8 (10.4) |
| Fatty liver | 4 (5.2) |
| Histology subtype, n (%) | |
| Leiomyosarcoma (LMS) | 25 (32.4) |
| Liposarcoma (LPS) | 4 (5.2) |
| Undifferentiated pleomorphic sarcoma (UPS)/myxofibrosarcoma (MFS) | 16 (20.8) |
| Angiosarcoma (AGS)/intimal sarcoma (IS) | 6 (7.8) |
| Round cell sarcoma/translocation‐related sarcoma (RCTS) b | 8 (10.4) |
| Malignant peripheral nerve sheath tumor (MPNST) | 5 (6.5) |
| Bone sarcoma (BS) | 6 (7.8) |
| Others | 7 (9.1) |
| Primary tumor location, n (%) | |
| Head and neck | 4 (5.2) |
| Trunk | 8 (10.4) |
| Extremities | 33 (42.9) |
| Abdominal and thoracic visceral organs | 22 (28.6) |
| Retroperitoneum | 10 (13.0) |
| Metastatic disease, n (%) | |
| Any metastasis | 73 (94.8) |
| Lung | 54 (70.1) |
| Liver | 11 (14.3) |
| Bone | 25 (32.5) |
| Brain | 5 (6.5) |
| Others | 36 (46.8) |
| Multiple metastatic sites (≥ 2) | 44 (57.1) |
| Pretreatment laboratory parameters, mean (95% CI) | |
| C‐reactive protein (mg/dL) | 3.1 (2.0–4.2) |
| Albumin (g/dL) | 3.7 (3.6–3.8) |
| Neutrophil‐lymphocyte ratio (NLR) | 5.5 (3.7–7.3) |
| Platelet‐lymphocyte ratio (PLR) | 177.3 (160.4–194.3) |
| Lymphocyte‐monocyte ratio (LMR) | 2.5 (2.2–2.9) |
| CRP‐albumin ratio (CAR) | 0.9 (0.59–1.28) |
| Systemic immune‐inflammation index (SII) a | 13.6 (13.4–13.8) |
| Lines of therapy at which G‐GDC + E was initiated, median (IQR) | 2 (2–3) |
Note: Natural logarithm of SII presented due to skewed distribution.
Abbreviations: CI, confidence interval; ECOG, Eastern Cooperative Oncology Group; G‐GDC + E, Gemcitabine‐Gemcitabine/Docetaxel/Cisplatin‐Everolimus; IQR, interquartile range.
SII = Platelet count × Neutrophil count/Lymphocyte count.
Round cell sarcoma/translocation‐related sarcoma = synovial sarcoma (SS), Ewings sarcoma (EWS), rhabdomyosarcoma (RMS), other round cell sarcomas.
The most common histologic subtypes were leiomyosarcoma (LMS, 32.4%), followed by undifferentiated pleomorphic sarcoma/myxofibrosarcoma (UPS/MFS, 20.8%), round cell sarcoma/translocation‐related sarcoma (RCTS, 10.4%), angiosarcoma/intimal sarcoma (AGS/IS, 7.8%), bone sarcoma (BS, 7.8%), malignant peripheral nerve sheath tumor (MPNST, 6.5%), and liposarcoma (LPS, 5.2%). Primary tumor sites included extremities (42.9%), abdominal and thoracic visceral organs (28.6%), retroperitoneum (13.0%), trunk (10.4%), and head and neck (5.2%).
Metastatic disease was present in 94.8% of patients, with lung (70.1%), bone (32.5%), and liver (14.3%) as common metastatic sites. Multiple metastatic sites were observed in 44 patients (57.1%). Baseline inflammatory biomarkers indicated elevated systemic inflammation, with a mean NLR of 5.5 (95% CI, 3.7–7.3), mean LMR of 2.5 (95% CI, 2.2–2.9), and mean CAR of 0.9 (95% CI, 0.59–1.28). The natural logarithm of SII (lnSII) had a mean value of 13.6 (95% CI: 13.4–13.8).
G‐GDC + E was administered as first‐line therapy in 14 patients (18.2%), second‐line therapy in 30 patients (39.0%), third‐line therapy in 22 patients (28.6%), and fourth‐line therapy or beyond in 11 patients (14.3%), with a median treatment line of 2 (IQR 2–3) (Table 1). Among patients who received G‐GDC + E as second line therapy or beyond (n = 63), the ifosfamide–epirubicin (IE) combination was the most common first‐line treatment across all subgroups. For patients treated with G‐GDC + E as third‐line therapy, pazopanib was the most frequent second‐line treatment (12/22, 54.5%), followed by trabectedin (5/22, 22.7%). In patients receiving G‐GDC + E as fourth‐line therapy or later, prior treatments were more heterogeneous, with pembrolizumab (3/11, 27.3%) and trabectedin (2/11, 18.2%) being the most common. Detailed information on prior treatment stratified by G‐GDC + E treatment line is provided in Table S3.
3.2. Treatment Outcomes
With a median follow‐up of 26.3 months (range, 1.5–154.7 months), the median OS was 16.8 months (95% CI, 13.6–23.9) (Figure S1a) and the median PFS was 5.4 months (95% CI, 4.3–8.3) (Figure S1b). The ORR was 45.5% (95% CI: 34.3–57.0), including CR in 3 patients (3.9%) and PR in 32 patients (41.6%). The DCR was 71.4% (95% CI: 60.0–80.8), with SD observed in 20 patients (26.0%) (Table 2).
TABLE 2.
Objective response and disease control with G‐GDC + E regimen.
| Response category | n (%) | 95% CI |
|---|---|---|
| Best overall response | ||
| Complete response (CR) | 3 (3.9) | |
| Partial response (PR) | 32 (41.6) | |
| Stable disease (SD) | 20 (26.0) | |
| Progressive disease (PD) | 22 (28.6) | |
| Efficacy measures | ||
| Objective response rate (CR + PR) | 35 (45.5) | 34.3–57.0 |
| Disease control rate (CR + PR + SD) | 55 (71.4) | 60.0–80.8 |
Abbreviations: CI, confidence interval; G‐GDC + E, gemcitabine, gemcitabine‐docetaxel‐cisplatin plus everolimus.
3.3. Histologic Subtype Analysis
Significant differences in treatment outcomes were observed across histologic subtypes. UPS/MFS demonstrated superior PFS compared to RCTS (median PFS: 7.8 vs. 3.6 months, p = 0.009, Figure 1a) and BS (median PFS: 7.8 vs. 2.3 months, p < 0.001, Figure 1a). LMS also showed better PFS than BS (median PFS: 5.9 vs. 2.3 months, p < 0.001. Figure 1b). Complete pairwise comparisons of median PFS across all histologic subtypes are listed in Table S1.
FIGURE 1.
Kaplan–Meier progression‐free survival (PFS) Curves by histologic subtypes. (a) PFS comparison between undifferentiated pleomorphic sarcoma/myxofibrosarcoma (UPS/MFS) and round cell sarcoma/translocation‐related sarcoma (RCTS) and bone sarcoma (BS). (b) PFS comparison between leiomyosarcoma (LMS) and BS.
These differences were further reflected in the 6‐month progression‐free rates (PFR) (Table 2). Each comparison row in Table S2 represents an independent pairwise analysis. UPS/MFS showed a significantly higher PFR compared to RCTS (81.2% vs. 25.0%, p = 0.007) and BS (81.2% vs. 14.3%, p = 0.003). LMS also demonstrated a higher PFR than RCTS (48.0% vs. 25.0%, p = 0.252) and BS (48.0% vs. 14.3%, p = 0.108), although these differences did not reach statistical significance.
Analysis of response rates by histology (Table S2) revealed that UPS/MFS had a notably higher ORR compared to BS (68.8% vs. 14.3%, p = 0.027) and showed a trend toward higher ORR compared to RCTS (68.8% vs. 37.5%, p = 0.204). Although differences in OS did not reach statistical significance in most pairwise comparisons, consistent trends favored LMS and UPS/MFS over BS and RCTS (Figure S2a,b).
3.4. Prognostic Significance of Inflammatory Biomarkers
Using ROC curve analysis, we determined optimal cut‐off values for inflammatory biomarkers (Table S4). The most discriminatory biomarkers were NLR (cut‐off: 2.705, AUC: 0.589, 95% CI: 0.453–0.725), LMR (cut‐off: 2.729, AUC: 0.590, 95% CI: 0.454–0.726), and CAR (cut‐off: 0.924, AUC: 0.595, 95% CI: 0.459–0.731).
Forest plot analysis (Figure 2) demonstrated that inflammatory biomarkers were significantly associated with OS. NLR ≥ 2.7 (HR = 2.04, 95% CI: 1.18–3.53, p = 0.011), LMR < 2.7 (HR = 2.31, 95% CI: 1.27–4.18, p = 0.006), and elevated lnSII ≥ 13.35 (HR = 2.06, 95% CI: 1.19–3.58, p = 0.010) were significantly associated with worse OS. CAR ≥ 0.924 showed a trend toward worse survival (HR = 1.51, 95% CI: 0.81–2.82, p = 0.194).
FIGURE 2.
Forest plot analysis of inflammatory biomarkers for overall survival. Hazard ratios with 95% confidence intervals for NLR ≥ 2.7, LMR < 2.7, ln(SII) ≥ 13.35, and CAR. CAR, C‐reactive protein‐to‐albumin ratio; LMR, lymphocyte‐to‐monocyte ratio; NLR, neutrophil‐to‐lymphocyte ratio; SII, systemic immune‐inflammation index.
K‐M survival analysis demonstrated significant prognostic value for several inflammatory biomarkers. NLR ≥ 2.7 was associated with significantly worse OS (p = 0.009) and worse PFS (p = 0.04) (Figure S3a,b). LMR < 2.7 demonstrated association with poor survival outcomes, showing significantly worse OS (p = 0.005) and a trend toward worse PFS (p = 0.13) (Figure S4a,b). Elevated lnSII ≥ 13.35 was significantly associated with worse OS (p = 0.009) and worse PFS (p = 0.036) (Figure S5a,b). PLR ≥ 159.4 showed trends toward worse survival in both OS (p = 0.17) and PFS (p = 0.16) (Figure S6a,b). CAR ≥ 0.924 demonstrated a trend toward worse OS (p = 0.203) but was not significantly associated with PFS (p = 0.579) (Figure S7a,b).
3.5. Impact of ECOG Performance Status on Survival
ECOG PS emerged as a powerful predictor of survival outcomes. Patients with ECOG PS ≥ 2 experienced significantly worse OS (median: 11.0 vs. 20.6 months, p < 0.001) and PFS (median: 2.1 vs. 7.4 months, p < 0.001) compared to those with ECOG PS 0–1 (Figure 3a,b). The separation of K‐M curves was evident early and persisted throughout the follow‐up period, highlighting the robust prognostic value of baseline performance status.
FIGURE 3.
Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Eastern Cooperative Oncology Group (ECOG) Performance Status (PS) < 2 and ≥ 2.
3.6. Multivariate Analysis of Prognostic Factors
Table 3 summarizes the univariate and multivariate Cox regression analyses of potential prognostic factors. In univariate analysis, factors significantly associated with worse OS included ECOG PS ≥ 2, unfavorable histology (RCTS + BS vs. LMS + UPS/MFS), lower albumin, elevated NLR (≥ 2.7), lower LMR (< 2.7), and higher lnSII (≥ 13.35).
TABLE 3.
Univariate and multivariate Cox regression analyses of prognostic factors.
| Variables | OS (overall survival) | PFS (progression free survival) | ||||||
|---|---|---|---|---|---|---|---|---|
| Univariate | Multivariate | Univariate | Multivariate | |||||
| HR (95% CI) | p | HR (95% CI) | p | HR (95% CI) | p | HR (95% CI) | p | |
| Clinical factors | ||||||||
| Male gender | 1.156 (0.670–1.994) | 0.603 | 1.195 (0.732–1.953) | 0.476 | ||||
| Age | 1.007 (0.985–1.029) | 0.533 | 0.989 (0.970–1.008) | 0.248 | ||||
| BW | 0.992 (0.975–1.010) | 0.409 | 0.998 (0.983–1.014) | 0.848 | ||||
| BMI | 0.950 (0.897–1.006) | 0.081* | 0.978 (0.914–1.046) | 0.508 | 0.976 (0.933–1.020) | 0.278 | ||
| ECOG PS ≥ 2 | 1.705 (0.928–3.130) | 0.085* | 2.377 (1.219–4.634) | 0.011** | 1.915 (1.077–3.405) | 0.027** | 2.229 (1.197–4.151) | 0.011** |
| DM | 0.944 (0.369–2.414) | 0.904 | 0.903 (0.442–1.843) | 0.778 | ||||
| HTN | 1.112 (0.599–2.064) | 0.737 | 1.458 (0.854–2.488) | 0.167 | ||||
| Dyslipidemia | 0.700 (0.252–1.948) | 0.495 | 0.874 (0.413–1.853) | 0.726 | ||||
| Fatty liver | 1.299 (0.400–4.212) | 0.663 | 1.165 (0.422–3.219) | 0.769 | ||||
| Location (extremity vs. others) | 0.647 (0.366–1.143) | 0.133 | 0.785 (0.480–1.284) | 0.334 | ||||
| Histology (LMS + UPS/MFS vs. RCTS + bone sarcoma) | 0.462 (0.218–0.979) | 0.044** | 0.404 (0.210–0.776) | 0.007** | 0.283 (0.144–0.562) | 0.001** | 0.468 (0.277–0.788) | 0.004** |
| Pretreatment metastasis | 1.194 (0.429–3.328) | 0.734 | 1.232 (0.294–2.242) | 0.688 | ||||
| Lung metastasis | 0.926 (0.528–1.622) | 0.787 | 1.410 (0.826–2.406) | 0.208 | ||||
| Liver metastasis | 1.697 (0.821–3.507) | 0.153 | 1.031 (0.479–1.965) | 0.933 | ||||
| Brain metastasis | 1.244 (0.492–3.143) | 0.644 | 2.971 (1.055–8.366) | 0.039** | 3.828 (1.334–10.987) | 0.013** | ||
| Over 1 metastatic sites | 0.999 (0.978–1.021) | 0.955 | 0.997 (0.625–1.596) | 0.995 | ||||
| Albumin | 0.533 (0.308–0.924) | 0.025** | 0.416 (0.221–0.784) | 0.007** | 0.819 (0.531–1.264) | 0.368 | ||
| Inflammatory biomarkers | ||||||||
| LDH | 1.002 (1.000–1.004) | 0.073* | 1.002 (1.000–1.005) | 0.052 | 1.001 (0.999–1.003) | 0.339 | ||
| CRP | 1.005 (0.989–1.021) | 0.535 | 0.995 (03979–1.012) | 0.595 | ||||
| NLR ≥ 2.7 | 2.054 (1.188–3.552) | 0.010** | 1.443 (0.196–2.445) | 0.568 | 1.592 (0.976–2.598) | 0.062* | 1.060 (0.306–1.893) | 0.894 |
| PLR ≥ 159.4 | 1.456 (0.839–2.528) | 0.182 | 1.459 (0.883–2.411) | 0.141 | 1.423 (0.818–2.477) | 0.212 | ||
| LMR < 2.7 | 2.322 (1.283–4.203) | 0.005** | 2.602 (1.319–5.134) | 0.006** | 1.454 (0.875–2.416) | 0.149 | 1.686 (0.923–3.082) | 0.089 |
| LnSII ≥ 13.35 | 2.060 (1.186–3.578) | 0.010** | 1.983 (0.596–6.597) | 0.264 | 1.544 (0.944–2.524) | 0.084* | 1.419 (0.612–3.288) | 0.567 |
| CAR ≥ 0.924 | 1.496 (0.802–2.791) | 0.206 | 1.167 (0.675–2.020) | 0.580 | ||||
Abbreviations: BH, body height; BMI, body mass index; BW, body weight; CAR, C‐reactive protein‐albumin ratio; CI, confidence interval; CRP, C‐reactive protein; DM, diabetes mellitus; ECOG PS, Eastern Cooperative Oncology Group performance status; HR, hazard ratio; HTN, hypertension; LDH, lactate dehydrogenase; LMR, lymphocyte‐to‐monocyte ratio; LMS, leiomyosarcoma; lnSII, natural logarithm of systemic immune‐inflammation index; MFS, myxofibrosarcoma; NLR, neutrophil‐to‐lymphocyte ratio; PLR, platelet‐to‐lymphocyte ratio; RCTS, round cell sarcoma/translocation‐related sarcoma; UPS, undifferentiated pleomorphic sarcoma.
*p < 0.1; **p < 0.05.
After adjusting for confounding factors in multivariate analysis, ECOG PS ≥ 2 (HR = 2.377, 95% CI: 1.219–4.634, p = 0.011), unfavorable histology (HR = 0.404, 95% CI: 0.210–0.776, p = 0.007), lower albumin (HR = 0.416, 95% CI: 0.221–0.784, p = 0.007), and lower LMR < 2.7 (HR = 2.602, 95% CI: 1.319–5.134, p = 0.006) emerged as independent predictors of worse OS.
For PFS, ECOG PS ≥ 2 (HR = 2.229, 95% CI: 1.197–4.151, p = 0.011), unfavorable histology (HR = 0.468, 95% CI: 0.277–0.788, p = 0.004), and brain metastases (HR = 3.828, 95% CI: 1.334–10.987, p = 0.013) were identified as independent prognostic factors.
3.7. Treatment‐Related Adverse Events
Treatment‐related AEs are summarized in Table 4. Hematologic toxicities were predominant, with thrombocytopenia in 75 patients (97.4%, Grade 3–4: 59.7%), neutropenia in 66 patients (85.7%, Grade 3–4: 68.8%), and anemia in 50 patients (64.9%, Grade 3–4: 49.4%). Febrile neutropenia occurred in 15 patients (19.5%).
TABLE 4.
Treatment‐related adverse events (N = 77).
| Adverse events | Any grade, n (%) | Grade 3–4, n (%) |
|---|---|---|
| Hematologic toxicities | ||
| Neutropenia | 66 (85.7) | 53 (68.8) |
| Febrile neutropenia | 15 (19.5) | |
| Thrombocytopenia | 75 (97.4) | 46 (59.7) |
| Anemia | 50 (64.9) | 38 (49.4) |
| Non‐hematologic toxicities | ||
| Fatigue | 56 (72.7) | 14 (18.2) |
| Nausea | 53 (68.8) | 8 (10.4) |
| Vomiting | 42 (54.5) | 6 (7.8) |
| Mucositis | 35 (45.5) | 6 (7.8) |
| Diarrhea | 30 (39.0) | 14 (18.2) |
| Skin toxicities | 33 (42.9) | 22 (28.6) |
| Peripheral neuropathy | 18 (23.4) | 3 (3.4) |
| Elevated transaminases | 15 (19.5) | 2 (2.6) |
| Pneumonitis | 6 (7.8) | 2 (2.6) |
| Treatment modifications | ||
| Dose reductions | 18 (23.4) | |
| Treatment delays | 25 (32.5) | |
Note: Adverse events were graded according to the Common Terminology Criteria for Adverse Events (CTCAE) version 5.0.
Common non‐hematologic toxicities included fatigue (72.7%; Grade 3–4: 18.2%), nausea (68.8%; Grade 3–4: 10.4%), vomiting (54.5%; Grade 3–4: 7.8%), mucositis (45.5%; Grade 3–4: 7.8%), skin toxicities (42.9%; Grade 3–4: 28.6%), and diarrhea (39.0%; Grade 3–4: 18.2%). Less frequent toxicities included peripheral neuropathy (23.4%), elevated transaminases (19.5%), and pneumonitis (7.8%).
Dose reductions were required in 18 patients (23.4%), and treatment delays occurred in 25 patients (32.5%). No treatment‐related deaths were recorded. No patients permanently discontinued G‐GDC + E because of treatment‐related AEs.
4. Discussion
In this study, we demonstrated that the G‐GDC + E regimen exhibited promising clinical activity in pre‐treated advanced or locally advanced STS, with an ORR of 45.5% and a median OS of 16.8 months. These results compare favorably to established subsequent lines therapies, where response rates typically range from 6% to 18% with median survival of 12–16 months [18, 19, 20, 21].
The combination of gemcitabine, docetaxel and platinum has demonstrated efficacy in non‐sarcoma cancer. In UC, gemcitabine‐docetaxel‐carboplatin achieves a 52.4% response rates in treatment‐naive patients [22]. In addition, this combination induce a ypCR rate of 38% in sarcomatoid variant [23]. In NSCLC, cisplatin‐gemcitabine‐docetaxel yields 52% response rates with median survival of 13.6 months [25]. In this study, we also showed the efficacy of G‐GDC + E in STS with an ORR of 45.5%.
The mTOR pathway has been identified as important for resistance to cytotoxic agents in preclinical and clinical studies. mTOR‐driven nucleotide synthesis, facilitated by increased pentose phosphate pathway activity and glycolytic reprogramming, can bypass gemcitabine‐induced metabolic stress [26, 27]. Upregulation of the mTOR pathway has been observed in docetaxel‐resistant prostate cancer [28] and head and neck cancer [29], and targeting this pathway may restore drug sensitivity [28, 29]. The mTOR pathway may contribute to cisplatin resistance in cancer cells through regulation of apoptosis, DNA repair, ferroptosis, and epithelial‐to‐mesenchymal transition (EMT) pathways [30].
In this study, weekly low‐dose everolimus (10 mg) was selected for potential modification of chemotherapy resistance, based on prior research. A phase I study indicated that weekly administration of everolimus at doses exceeding 20 mg inhibited S6 kinase 1 activity in peripheral‐blood mononuclear cells for at least 7 days but was associated with significant toxicity [55]. Another phase I trial evaluating everolimus (20–50 mg) combined with docetaxel on days 1 and 8 was discontinued due to a high rate of neutropenia [56]. Additionally, extended mTOR inhibition has been observed to cause AKT feedback activation [57]. Furthermore, a phase II study found that incorporating weekly 10 mg everolimus with cisplatin plus high‐dose 5‐fluorouracil was associated with prolonged progression‐free survival in treatment‐naïve patients with advanced gastric cancer [58]. Therefore, weekly 10 mg everolimus is a reasonable choice.
Sarcomas are a group of heterogeneous tumors which show diverse biology and response to treatment [1, 2]. Our histologic analysis demonstrates superior UPS/MFS outcomes, aligning with established GD literature. Bay et al. reported 36% UPS and 32% LMS response rates versus 25% SS and 14% LPS, with superior PFS in UPS (7.0 months) and LMS (6.5 months) [14]. SARC002 validated this selectivity with 24.1% LMS and 23.1% UPS responses versus 10.5% SS and 8.3 LPS, with significant LMS PFS improvement (6.2 vs. 3.0 months, p = 0.02) [59]. TAXOGEM confirmed LMS efficacy (PFS 5.5 vs. 3.0 months, p = 0.0002) [60], while Hensley demonstrated 53% response rates in gynecologic LMS [11, 13].
Previous studies had demonstrated the efficacy of the GD regimen in conventional osteosarcoma. Navid et al. reported 58% response rates of the GD combination in relapsed tumors [61], while Children's Oncology Group studies demonstrated 11%–17% single‐agent gemcitabine responses in recurrent disease [62]. However, our small BS cohort (n = 6), which comprised malignant giant cell tumor (n = 2), parosteal OGS (n = 2), low grade OGS (n = 1), and mesenchymal chondrosarcoma (n = 1), demonstrated the poorest outcomes among all histologic subtypes. The limited efficacy may be attributed to stromal cells with cancer stem cell characteristics [63], activation of anti‐apoptotic pathways [64, 65] and aberrant cell cycle regulation [65, 66]. Nevertheless, further studies are warranted to elucidate the underlying mechanisms of resistance of these subtypes of BS to the G‐GDC + E regimen.
Inflammatory biomarkers have been shown to have prognostic impacts on a variety of cancer types. In metastatic UC, elevated pretreatment NLR has been reported as an independent predictor of inferior PFS and OS in patients receiving cisplatin‐based chemotherapy [46]. In stage IV NSCLC, elevated NLR and PLR, and reduced LMR, have been associated with inferior survival in patients undergoing first‐line therapy [47].
In this study, we also identified inflammatory biomarkers as independent prognostic factors. The particularly strong association of LMR < 2.7 with poor OS is noted. In a study regarding 149 advanced STS patients treated with first‐line doxorubicin, Watanabe et al. found that LMR significantly correlated with the tumoral CD3/CD68‐positive cell ratio (R = 0.959, p = 0.04). In addition, low LMR was independently associated with worse OS (HR 3.93, p = 0.001) [48]. Similar correlations have been reported in hepatocellular carcinoma [67], indicating that low peripheral LMR corresponds to reduced T‐cell infiltration and increased macrophage presence within tumors [48]. Additionally, LMR has been reported to be associated with elevated PD‐L1 expression in tumor tissues across multiple malignancies [68, 69]. Therefore, low LMR may serve as a surrogate marker for immunosuppressive tumor microenvironments, potentially explaining the inferior survival outcomes observed in patients with low LMR values. However, these relationships remain correlative and require further validation.
ECOG PS emerged as a powerful predictor of both OS (HR = 2.377, p = 0.011) and PFS (HR = 2.229, p = 0.011), with patients having PS ≥ 2 experiencing markedly inferior outcomes. This finding underscores the critical importance of treatment timing, suggesting that therapeutic intervention should be initiated before significant functional decline occurs. The independent prognostic significance of albumin levels (HR = 0.416, p = 0.007) reflects the importance of nutritional status and physiological reserve in advanced STS patients. Hypoalbuminemia may indicate cachexia, liver dysfunction, or systemic inflammation, all of which compromise treatment tolerance and survival outcomes [70].
The G‐GDC + E regimen demonstrated significant toxicity. The near‐universal occurrence of thrombocytopenia (97.4%, Grade 3–4: 59.7%) reflects cumulative myelosuppressive effects [71, 72, 73]. In addition, an 18.2% rate of Grade 3–4 diarrhea was observed, consistent with previous reports regarding everolimus [74]. A NSCLC study also showed that everolimus addition to paclitaxel plus carboplatin increased both thrombocytopenia and diarrhea regardless of bevacizumab co‐administration [75]. The absence of treatment‐related mortality, together with the effective management of AEs—including dose reductions in 23.4% of patients and treatment delays in 32.5%—suggests that the toxicities associated with G‐GDC + E were generally controllable with close monitoring. AEs were addressed through dose modifications, cycle delays, granulocyte colony‐stimulating factor support, transfusion therapy, and proactive supportive interventions, such as antidiarrheal prophylaxis and dermatologic care. No patients permanently discontinued G‐GDC + E because of treatment‐related AEs, and these strategies enabled all patients to maintain treatment continuity.
This study has several limitations. The retrospective single‐institution design introduces selection bias and limits generalizability. The modest sample size restricts definitive subgroup conclusions. The lack of formal phase I dose‐finding studies represents a significant limitation, as the dosing rationale was empirically derived rather than systematically optimized. The evaluation of response and toxicity retrospectively may have resulted in under‐reporting compared to prospective trials. The lack of a control group prevents direct comparative assessment of efficacy and safety against standard therapies. The absence of prospectively collected patient‐reported outcomes (PROs) prevents comprehensive evaluation of treatment impact on quality of life, symptom burden, and functional status.
Future research should include prospective multicenter validation with randomized comparison against established second‐line options. Also, prospective validation studies should incorporate validated PRO tools (e.g., EORTC QLQ‐C30, FACT‐G) to comprehensively assess the patient experience beyond objective toxicity metrics. Molecular profiling studies could identify predictive biomarkers for personalized treatment approaches. The strong prognostic significance of inflammatory markers warrants investigation into interventional strategies targeting these factors.
In conclusion, the G‐GDC + E regimen demonstrates meaningful activity in advanced and metastatic STS with 45.5% ORR and 16.8 months median OS, comparing favorably to established second‐line therapies. ECOG PS ≥ 2 and LMR < 2.7 emerged as independent predictors of poor survival, enabling clinical risk stratification. UPS/MFS showed superior responses, supporting histology‐guided patient selection. The toxicity profile, while significant with near‐universal thrombocytopenia and notable diarrhea, was clinically controllable through dose modification, course delay, and supportive care. Prospective validation through randomized trials is essential to establish G‐GDC + E's definitive role in STS treatment algorithms.
Author Contributions
W.‐C.W. and C.‐C.Y. were responsible for the design and conception of the study. W.‐C.W. and I.‐W.H. were responsible for data acquisition. S.‐C.C., P.C.‐H.C., P.‐K.W., C.‐M.C., and H.‐T.W. were responsible for data interpretation. W.‐C.W. was responsible for writing the original draft of the manuscript. C.‐J.L., T.‐C.C., and C.‐C.Y. reviewed and edited the manuscript. W.‐C.W. and C.‐C.Y. confirmed the authenticity of all the raw data. All authors read and approved the final version of the manuscript.
Funding
This work was sponsored by the funding of Yin Shu‐Tien Foundation Taipei Veterans General Hospital‐National Yang Ming Chiao Tung University Excellent Physician Scientists Cultivation Program (No. 113‐V‐A‐002) and Melissa Lee Cancer Foundation to WCW; it was also partly supported by grants from the National Science and Technology Council (grant nos. MOST 110‐2314‐B‐075‐070, MOST 111‐2314‐B‐075‐022, NSTC 114‐2314‐B‐075‐075), Taipei Veterans General Hospital (grant nos. V110D56‐002‐MY2‐1, V110D56‐002‐MY2‐2, V110C‐208, V112C‐093, V113C‐116, V114D78‐002‐MY2‐1), and Melissa Lee Cancer Foundation (grant no. MLCF_V114_A11403) to C.‐C.Y.
Ethics Statement
This retrospective study was approved by the Institutional Review Board of Taipei Veterans General Hospital (Approval Number: 2024‐10‐002ACF) and was conducted in accordance with the Declaration of Helsinki, Good Clinical Practice guidelines, and local regulatory requirements. Due to the retrospective nature of this study, the requirement for informed consent was waived by the ethics committee.
Conflicts of Interest
The authors declare no conflicts of interest.
Supporting information
Table S1: Pairwise comparisons of response outcomes across histologic subtypes.
Table S2: Pairwise comparisons of response outcomes across histologic subtypes.
Table S3: Prior systemic therapies administered before Gemcitabine‐Gemcitabine/Docetaxel/Cisplatin‐Everolimus.
Table S4: Discriminatory performance of inflammatory biomarkers for 1‐year overall survival.
Figure S1: Kaplan–Meier survival curves for patients with advanced sarcoma treated with Gemcitabine‐Docetaxel‐Cisplatin + Everolimus (G‐GDC + E) regimen. (a) Overall survival (OS). (b) Progression‐free survival (PFS). Numbers at risk shown below each time point.
Figure S2: (a) Kaplan–Meier analysis comparing overall survival (OS) between undifferentiated pleomorphic sarcoma/myxofibrosarcoma (UPS/MFS, green), round cell sarcoma/translocation‐related sarcoma (RCTS, red), and bone sarcoma (BS, blue). (b) Kaplan–Meier analysis comparing OS between leiomyosarcoma (LMS, green), RCTS (red), and BS (blue).
Figure S3: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Neutrophil‐to‐Lymphocyte Ratio (NLR) < 2.7 and ≥ 2.7.
Figure S4: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Lymphocyte‐to‐Monocyte Ratio (LMR) < 2.7 and ≥ 2.7.
Figure S5: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Natural Logarithm of Systemic Immune‐Inflammation Index (lnSII) < 13.35 and ≥ 13.35.
Figure S6: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Platelet‐to‐Lymphocyte Ratio (PLR) < 159.4 and ≥ 159.4.
Figure S7: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with C‐reactive protein‐to‐albumin ratio (CAR) < 0.924 and ≥ 0.924.
Acknowledgments
The authors thank the staff of the Department of Pathology, Taipei Veterans General Hospital for their assistance with histology acquisition and interpretation.
Data Availability Statement
The data that supports the findings of this study are available on request from the corresponding author, C.‐C.Y.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Table S1: Pairwise comparisons of response outcomes across histologic subtypes.
Table S2: Pairwise comparisons of response outcomes across histologic subtypes.
Table S3: Prior systemic therapies administered before Gemcitabine‐Gemcitabine/Docetaxel/Cisplatin‐Everolimus.
Table S4: Discriminatory performance of inflammatory biomarkers for 1‐year overall survival.
Figure S1: Kaplan–Meier survival curves for patients with advanced sarcoma treated with Gemcitabine‐Docetaxel‐Cisplatin + Everolimus (G‐GDC + E) regimen. (a) Overall survival (OS). (b) Progression‐free survival (PFS). Numbers at risk shown below each time point.
Figure S2: (a) Kaplan–Meier analysis comparing overall survival (OS) between undifferentiated pleomorphic sarcoma/myxofibrosarcoma (UPS/MFS, green), round cell sarcoma/translocation‐related sarcoma (RCTS, red), and bone sarcoma (BS, blue). (b) Kaplan–Meier analysis comparing OS between leiomyosarcoma (LMS, green), RCTS (red), and BS (blue).
Figure S3: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Neutrophil‐to‐Lymphocyte Ratio (NLR) < 2.7 and ≥ 2.7.
Figure S4: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Lymphocyte‐to‐Monocyte Ratio (LMR) < 2.7 and ≥ 2.7.
Figure S5: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Natural Logarithm of Systemic Immune‐Inflammation Index (lnSII) < 13.35 and ≥ 13.35.
Figure S6: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with Platelet‐to‐Lymphocyte Ratio (PLR) < 159.4 and ≥ 159.4.
Figure S7: Kaplan–Meier analysis comparing (a) overall survival (OS) and (b) progression‐free survival (PFS) between patients with C‐reactive protein‐to‐albumin ratio (CAR) < 0.924 and ≥ 0.924.
Data Availability Statement
The data that supports the findings of this study are available on request from the corresponding author, C.‐C.Y.