Abstract
PURPOSE
We tested the hypothesis that adding metastasis-directed therapy (MDT) to standard-of-care (SOC) systemic therapy improves progression-free survival (PFS) among patients with oligometastatic disease.
METHODS
EXTEND was a multicenter randomized phase II trial. Patients with 1–5 metastases were randomly assigned to MDT + SOC versus SOC in one of the six baskets (breast, pancreas, kidney, two prostate baskets, and an other basket) with basket-specific stratification and powering. PFS, the primary end point, was prespecified in the per-protocol set within each basket, across all baskets, and across all baskets excluding the prostate baskets. Exploratory end points included circulating tumor DNA (ctDNA) and immune profiling.
RESULTS
From 2018 through 2023, 521 patients were screened, 350 were randomly assigned, and 334 were analyzed per protocol (MDT + SOC, n = 166; SOC, n = 168). Radiotherapy was used as MDT for 98% of metastases (370/379). Overall, after a median follow-up of 53 months, PFS was improved with MDT + SOC (hazard ratio [HR], 0.54 [95% CI, 0.41 to 0.72], P < .001). Similarly, PFS was improved when excluding the prostate baskets (HR, 0.60 [95% CI, 0.40 to 0.89]). Within each basket, PFS superiority was identified for the pancreas, prostate, and other baskets, whereas the breast and kidney baskets were inconclusive. At enrollment, detectable ctDNA correlated with shorter PFS and survival; by contrast, ctDNA clearance 3 months postenrollment correlated with improved survival. MDT + SOC-induced systemic immune activation was most pronounced among baskets demonstrating PFS superiority.
CONCLUSION
The phase II EXTEND trial supports the addition of MDT to SOC for oligometastatic disease. Histology-specific efficacy signals were identified for phase III testing. Translational insights suggest the potential for optimizing the definition of oligometastasis using ctDNA and point to systemic immune responses as a possible mechanism of benefit from MDT.
INTRODUCTION
Oligometastatic disease has been postulated as a clinical opportunity to intervene with metastasis-directed therapy (MDT) and meaningfully impact the natural history of metastatic cancer.1 SABR-COMET provided foundational evidence supporting the integration of MDT with standard-of-care (SOC) systemic therapy.2,3 However, a potential criticism of SABR-COMET was a lack of tumor-type stratification. As considerable heterogeneity exists in biology and responses to systemic therapies among different tumor types, we initiated the EXTEND trial to test the hypothesis adding MDT to SOC would improve progression-free survival (PFS). Five histology-specific baskets were chosen based on pragmatic assessment of accrual feasibility in a single-arm, lead-in phase for independent powering and assessment.4 A sixth other basket was powered for histologies not selected for individual baskets. We previously reported the primary analyses for the breast, pancreatic, and two prostate cancer baskets.5–8
In this study, we report the primary aggregated analysis of all randomly assigned patients and the primary findings of the kidney and other baskets. Patient follow-up in previously reported baskets has been updated to correspond with a single data cut-off date across all baskets. Circulating tumor DNA (ctDNA) was evaluated to identify patients most likely to benefit from MDT, and immune profiles were investigated to study the potential mechanism of action underlying systemic benefit from MDT.
METHODS
Trial Design
EXTEND (ClinicalTrials.gov identifier: NCT03599765) was an investigator-initiated, multicenter, open-label, parallel group, superiority-design phase II randomized trial of patients with oligometastatic solid tumors. Eligible patients had 1–5 metastases amenable to MDT, ≤4 prior lines of systemic therapy for metastatic disease, and 1 of 12 histologies (Data Supplement, Table S1, online only). Following consent, patients were equally randomly assigned to MDT + SOC or SOC without masking using a dynamic random assignment method from Pocock and Simon within a clinical trial management system housed by the Department of Biostatistics.9 Prior lines of systemic therapy (0–1 v 2–4) and number of metastases (1–2 v 3–5) were used for stratification in all baskets. Additional stratification factors were uniquely applied to each basket (Data Supplement).
Procedures
SOC included systemic therapy or observation at the discretion of the treating medical oncologist. In the prostate cancer baskets, androgen deprivation therapy (ADT) included gonadotropin-releasing hormone agonism or antagonism with or without androgen receptor pathway inhibition. ADT was given for 6 months and then held in the intermittent ADT basket or given indefinitely until progression in the continuous ADT basket.7,8 MDT could include radiotherapy, resection, or ablation. Follow-up assessments were obtained at baseline and 3-month intervals after enrollment. In the prostate cancer baskets, prostate-specific antigen (PSA) was obtained at follow-up intervals, and imaging was obtained when PSA was ≥1 ng/mL over nadir.7,8
Outcomes
The primary end point was PFS defined by RECIST v1.1 radiologic progression measured by blinded central review (MD Anderson Quantitative Imaging Core), clinical progression, or death. Clinical progression was determined by the treating physicians. In the prostate cancer baskets, PSA progression per Prostate Cancer Working Group Criteria was also considered a PFS event to be pragmatic and align to standard clinical practice.7,8 Secondary end points included overall survival (OS), disease-specific survival (DSS), time to next-line systemic therapy, time to new lesion formation, and local control. End point comparisons were prespecified within each basket and three pooled populations: (1) an aggregated analysis, (2) an aggregated analysis of all baskets except prostate cancer, and (3) an aggregated analysis of prostate cancer. Prostate cancer was distinguished based on expectations for more favorable outcomes and differences in sample size.
Other end points were toxicity, defined by the Common Terminology Criteria for Adverse Events v4.0, and patient-reported outcomes. Serial plasma at enrollment, end of MDT, 3-month follow-up, and progression was collected for exploratory measures. The tumor-agnostic methylation-based tissue-free Guardant Reveal assay was used for ctDNA (Guardant Health).10 In brief, cell-free DNA was isolated, separated according to methylation status, and enriched for CpG-rich regulatory sequences known to be unmethylated in healthy patients.10 Methylated ctDNA tumor fraction was estimated by normalizing cancer-specific differentially methylated regions with matched control regions within each sample.10,13 Immune profiling was performed using multiparametric flow cytometry, electro-chemiluminescent enzyme-linked immunosorbent assay for cytokines (Meso Scale Discovery), and T-cell receptor (TCR) sequencing using immunoSEQ (Adaptive Biotechnologies; Data Supplement).7,8,11,12
Statistical Analysis
The Gomez et al14 trial, which represented the only randomized trial in oligometastasis before protocol development, identified median PFS increase from 4 months to 12 months in non–small cell lung cancer. The nonprostate cancer baskets were thus powered to detect improvements in median PFS from 4 to 8.5 months, requiring 40 patients per basket to achieve 80% power with 1-sided log-rank and 0.10 type I error (chosen for efficiency of the signal-finding design).14 On the basis of expectations for longer PFS in the prostate baskets, 87 patients were needed to demonstrate median PFS improvement from 18 to 36 months. PFS significance was defined by 1-sided log-rank as P < .10; for other end points, 2-sided log-rank P < .05 was used. Two-sided P are presented throughout for ease of interpretation.
For non-DSS efficacy end points, arms were compared with stratified log-rank and Cox. For DSS, stratified proportional hazards using Fine-Gray test for competing risks was used. Stratification factors for the basket-level analyses were the same as those used at random assignment; for aggregated analyses, stratification factors were the common factors plus basket identity. OS was analyzed intention to treat; other end points were prespecified for the per-protocol population. Crossover to MDT following progression after SOC was permitted; secondary end points did not prespecify crossover effect adjustment. Patient-reported outcomes were analyzed with mixed-effect models adjusting for baseline. Post hoc and translational P are presented descriptively. Analyses were performed with SAS v9.4 (Cary, NC) and R v4.3.1 (Vienna, Austria).
RESULTS
Patient Characteristics
Between September 2018 and August 2023, 521 patients were screened and 350 randomly assigned (Data Supplement, Figs S1–S7). Twelve patients declined allocation and four no longer met inclusion criteria, resulting in 334 patients in the per-protocol population (Data Supplement, Fig S1). Most had 1–2 metastases (63%) with metachronous presentation (67%) and fewer than two prior systemic therapy lines (82%; Table 1; Data Supplement, Table S1). The most common MDT modality was radiation therapy (98%), typically stereotactic body radiation therapy (51%; Data Supplement, Table S2). SOC included systemic therapy in 97% (Data Supplement, Table S3).
TABLE 1.
Patient Demographics and Characteristics in the Per-Protocol Population
| Characteristic | Overall | MDT + SOC | SOC |
|---|---|---|---|
| Aggregate, No. (%) | 334 (100) | 166 (100) | 168 (100) |
| Basket, No. (%) | |||
| Breast | 40 (12) | 20 (12) | 20 (12) |
| Pancreas | 40 (12) | 19 (11) | 21 (13) |
| Prostate iADT | 87 (26) | 43 (26) | 44 (26) |
| Prostate cADT | 87 (26) | 45 (27) | 42 (25) |
| Kidney | 40 (12) | 20 (12) | 20 (12) |
| Other | 40 (12) | 19 (11) | 21 (13) |
| Age, years, median (IQR) | 67 (61–72) | 67 (61–72) | 66 (60–72) |
| Sex, male, No. (%) | 246 (74) | 120 (72) | 126 (75) |
| Race/ethnicity, No. (%) | |||
| Non-Hispanic Caucasian | 249 (75) | 131 (79) | 118 (70) |
| Hispanic | 38 (11) | 18 (11) | 20 (12) |
| Black | 27 (7) | 8 (5) | 19 (11) |
| Other/unknown | 20 (6) | 9 (5) | 11 (7) |
| Number of metastases, No. (%) | |||
| 1–2 | 212 (63) | 103 (62) | 109 (65) |
| 3–5 | 122 (37) | 63 (38) | 59 (35) |
| Organs involved, No. (%) | |||
| Bone | 157 (47) | 82 (49) | 75 (45) |
| Lung | 60 (18) | 32 (19) | 28 (17) |
| Lymph node | 143 (43) | 70 (42) | 73 (44) |
| Liver | 41 (12) | 19 (11) | 22 (13) |
| Other | 22 (7) | 11 (6) | 11 (7) |
| Prior lines of systemic therapy, No. (%) | |||
| 0–1 | 273 (82) | 136 (82) | 137 (82) |
| 2–4 | 61 (18) | 30 (18) | 31 (18) |
| Primary tumor present, No. (%) | 106 (32) | 56 (34) | 50 (30) |
| Oligometastatic state, No. (%) | |||
| Metachronous | 225 (67) | 107 (64) | 118 (70) |
| Synchronous | 104 (31) | 54 (33) | 50 (30) |
| Induced | 5 (2) | 5 (3) | 0 (0) |
| Enrollment site, No. (%) | |||
| Texas medical center | 238 (72) | 119 (72) | 119 (71) |
| Houston area location | 55 (16) | 29 (17) | 26 (15) |
| Network | 41 (12) | 18 (11) | 23 (13) |
Abbreviations: ADT, androgen deprivation therapy; MDT, metastasis-directed therapy; SOC, standard of care.
Primary End Point
Data were locked on April 1, 2025. In the aggregated analysis, after median follow-up of 53 months (IQR, 38–60), PFS was significantly longer after MDT + SOC than SOC (hazard ratio [HR], 0.54 [95% CI, 0.41 to 0.72]; P < .001; Fig 1A; Table 2). Schoenfeld residual did not strongly refute the proportional hazards assumption (P = .10). Nonetheless, given the potential time-dependent HR, restricted mean survival time (RMST) analyses were performed post hoc and were consistent with the main analysis (Data Supplement, Table S4). Post hoc–modified PFS (excluding PSA-only event criteria) showed similar findings to the main analysis (HR, 0.63 [95% CI, 0.48 to 0.84]; P = .002). In the aggregated population excluding prostate cancer, PFS was longer (HR, 0.60 [95% CI, 0.40 to 0.89]; P = .01; Fig 1B; Table 2). PFS was improved in the other histology basket (HR, 0.41 [95% CI, 0.17 to 0.99]; P = .04; Data Supplement, Fig S8; Table 2). In the kidney basket, the effect was inconclusive (HR, 1.03 [95% CI, 0.46 to 2.33]; P = .93; Data Supplement, Fig S8; Table 2). The median PFS was 10.7 versus 11.8 months, exceeding powering estimates (ie, 8.5 v 4 months). MDT + SOC demonstrated superior PFS in the pancreas and both prostate baskets and was inconclusive in the breast basket (Fig 1C; Data Supplement, Fig S8; Table 2). Event counts and post hoc multiplicity-adjusted P values are presented (Data Supplement, Table S5 and S6).
FIG 1.
Primary end point of PFS. (A) PFS in the aggregated analysis of all baskets. (B) PFS in the aggregated analysis of all baskets excluding prostate cancer baskets. (C) Forest plot of PFS in all individual and aggregated baskets. ADT, androgen deprivation therapy; HR, hazard ratio; MDT, metastasis-directed therapy; PFS, progression-free survival; SOC, standard of care.
TABLE 2.
Summary of Primary and Secondary Efficacy End Points
| PFS Time, Median (95% CI) | ||||
|---|---|---|---|---|
| Basket (median follow-up time) | HR (95% CI) | P | MDT + SOC | SOC |
| Breast (46 months) | ||||
| PFS | 0.73 (0.29 to 1.83) | .497 | 23.33 (11.63 to NE) | 24.94 (11.07 to NE) |
| OS | 1.98 (0.46 to 8.55) | .351 | NE | NE |
| Time to NLST | 0.46 (0.14 to 1.49) | .186 | NE | 37.8 (21.78 to NE) |
| Time to new lesion | 0.92 (0.37 to 2.29) | .857 | 23.32 (11.63 to NE) | 24.94 (15.67 to NE) |
| DSS | 1.66 (0.46 to 6.08) | .441 | — | — |
| Kidney (42 months) | ||||
| PFS | 1.03 (0.46 to 2.33) | .931 | 10.66 (6.18 to 24.51) | 11.84 (6.9 to 19.78) |
| OS | 5.38 (1.04 to 27.8) | .032 | 48.16 (31.77 to NE) | NE |
| Time to NLST | 0.90 (0.33 to 2.46) | .843 | 27.33 (14.52 to NE) | 37.02 (16.82 to NE) |
| Time to new lesion | 1.37 (0.55 to 3.40) | .497 | 23.42 (10.71 to NE) | 32.42 (12.45 to NE) |
| DSS | 5.34 (1.07 to 26.97) | .041 | — | — |
| Pancreatic (30 months) | ||||
| PFS | 0.40 (0.19 to 0.84) | .012 | 10.64 (5.88 to NE) | 2.53 (1.74 to 7.36) |
| OS | 0.90 (0.42 to 1.93) | .787 | 13.54 (9.59 to 26.91) | 11.33 (7.59 to NE) |
| Time to NLST | 0.52 (0.18 to 1.45) | .204 | 18.99 (12.65 to NE) | 20.90 (5.91 to NE) |
| Time to new lesion | 0.79 (0.27 to 2.27) | .655 | NE | 27.01 (4.01 to NE) |
| DSS | 0.48 (0.20 to 1.12) | .089 | — | — |
| Prostate cADT (43 months) | ||||
| PFS | 0.56 (0.28 to 1.09) | .082 | 41.4 (36.34 to NE) | 24.54 (16.76 to 45.27) |
| OS | 0.64 (0.24 to 1.71) | .372 | NE | NE |
| Time to NLST | 1.08 (0.50 to 2.30) | .850 | NE | NE |
| Time to new lesion | 0.96 (0.45 to 2.03) | .905 | NE | NE |
| DSS | 1.36 (0.49 to 3.80) | .555 | — | — |
| Prostate iADT (58 months) | ||||
| PFS | 0.44 (0.25 to 0.77) | .003 | 28.39 (23.59 to 47.9) | 15.77 (14 to 22.6) |
| OS | 0.41 (0.12 to 1.39) | .140 | 68.9 (68.86 to NE) | 70.93 (70.93 to NE) |
| Time to NLST | 0.48 (0.22 to 1.04) | .059 | NE | NE |
| Time to new lesion | 0.63 (0.35 to 1.13) | .120 | 36.60 (28.39 to NE) | 23.98 (17.68 to NE) |
| DSS | 0.14 (0.01 to 1.30) | .083 | — | — |
| Other (50 months) | ||||
| PFS | 0.41 (0.17 to 0.99) | .043 | 17.08 (10.74 to NE) | 8.74 (5.82 to NE) |
| OS | 0.64 (0.25 to 1.64) | .345 | 41.00 (29.63 to NE) | 42.35 (23.29 to NE) |
| Time to NLST | 0.86 (0.33 to 2.24) | .750 | 24.71(19.55 to NE) | 22.64 (8.84 to NE) |
| Time to new lesion | 0.76 (0.30 to 1.95) | .586 | 34.73 (12.65 to NE) | 13.17 (8.18 to NE) |
| DSS | 0.43 (0.16 to 1.17) | .098 | — | — |
| Aggregated (53 months) | ||||
| PFS | 0.54 (0.41 to 0.72) | <.001 | 25.40 (19.98 to 33.31) | 14.00 (12.16 to 16.76) |
| OS | 0.96 (0.65 to 1.41) | .815 | 68.86 (67.98 to NE) | 70.93 (59.37 to NE) |
| Time to NLST | 0.71 (0.50 to 1.02) | .062 | 64.69 (49.91 to NE) | 47.11 (35.15 to NE) |
| Time to new lesion | 0.90 (0.66 to 1.23) | .498 | 36.34 (28.39 to 47.11) | 27.79 (22.01 to 45.31) |
| DSS | 0.82 (0.53 to 1.25) | .351 | — | — |
| Aggregated excluding prostate (45 months) | ||||
| PFS | 0.60 (0.40 to 0.89) | .010 | 14.00 (10.71 to 18.89) | 8.48 (6.08 to 13.17) |
| OS | 1.24 (0.77 to 2.02) | .375 | 38.28 (26.71 to NE) | 49.71 (37.45 to NE) |
| Time to NLST | 0.67 (0.41 to 1.10) | .113 | 32.13 (0.39 to 0.63) | 23.13 (21.78 to NE) |
| Time to new lesion | 1.03 (0.65 to 1.62) | .910 | 20.99 (15.64 to 41.79) | 20.63 (13.17 to 39.20) |
| DSS | 0.98 (0.60 to 1.60) | .935 | — | — |
NOTE. HRs with 95% CI are from stratified Cox regressions, and P values are from the stratified log-rank tests except DSS. For DSS, subdistribution HRs and P values are provided from stratified proportional subdistribution hazards models. For consistency throughout the table, all P values presented here are two-sided, although for PFS, significance was defined using one-sided P.
Abbreviations: ADT, androgen deprivation therapy; cADT, continuous ADT; DSS, disease-specific survival; HR, hazard ratio; iADT, intermittent ADT; MDT, metastasis-directed therapy; NE, not estimable; NLST, next line systemic therapy; OS, overall survival; PFS, progression-free survival; SOC, standard of care.
The aggregate HR point estimate was encompassed within the 95% CI of each basket, suggesting limited evidence for basket-level differential treatment effects (Fig 1C).15–17 Post hoc subgroup analysis in the aggregate population suggested potential heterogeneity according to prior lines and liver involvement (Data Supplement, Fig S9). The relative benefit of MDT + SOC was greater among patients with 0 to 1 prior lines versus 2 to 4 prior lines (interaction P = .006); within each basket, this interaction was only observed in the kidney basket (interaction P = .002). Potentially greater benefit of MDT + SOC was suggested among patients with liver metastases (interaction P = .02).
Secondary End Points
No statistically significant differences were found for time to new lesion or time to next line systemic therapy (Data Supplement, Figs S10 and S11). In the MDT + SOC arm, there were 21 local failures, yielding crude per-patient and perlesion proportions of 13% and 6%, respectively (Data Supplement, Table S7). At first progression after SOC, 51% of patients (66/129) received crossover MDT. OS and DSS were not significantly improved with MDT + SOC (Data Supplement, Figs S12 and S13). Given the proportion of crossover potentially introducing time-dependent effects, post hoc RMST was performed and demonstrated consistency with the main analysis (Data Supplement, Table S8). In the kidney basket, both OS and DSS were shorter after MDT + SOC (Data Supplement, Figs S12–S13). There were 10 deaths in the MDT + SOC arm and four in the SOC arm, with 10 and 3 deaths attributed to disease. Post hoc sensitivity analysis, after excluding one unevaluable patient in the SOC arm (who withdrew shortly after random assignment) and one evaluable patient in the MDT + SOC (who died shortly after random assignment before study treatments), did not contradict the supposition that SOC and MDT + SOC yield the same OS (HR, 4.07 [95% CI, 0.77 to 21.6]; P = .08) or DSS (subdistribution HR, 4.07 [95% CI, 0.80 to 20.67]; P = .09). There were no appreciable random differences in the baseline clinical covariates between arms (Data Supplement, Table S9).
No significant differences were observed in grade ≥3 adverse events (n = 10 [6%] v n = 4 [2%], P = .11; risk difference 3.6% [95% CI, −0.7% to 8%]; Data Supplement, Table S10 and S11). Quality of life was not worsened by MDT + SOC, and no significant interactions between time and treatment favoring MDT+SOC were observed.
Circulating Tumor DNA
Of 554 samples, 550 (99.3%) met quality control. A total of 237 patients had profiling at enrollment (Data Supplement, Table S12). Of these, ctDNA was detected (ctDNA[+]) in 115 (49%), despite most patients being on systemic therapy. Rates of ctDNA(+) were higher in the other histology (79%) and pancreas (70%) baskets (Data Supplement, Fig S14). Number of prior lines and lymph node metastases were associated with ctDNA(+) (Data Supplement, Table S13). Among the prostate baskets, PSA was associated with ctDNA(+) and methylated ctDNA tumor fraction burden; interestingly five patients had undetectable PSA with detectable ctDNA(+) (out of 41 patients with undetectable PSA or 12%; Data Supplement, Table S13 and Fig S15). TP53 (n = 66), NF1 (n = 18), and ATM (n = 18) were most typical alterations.
Adjusted for arm, basket, and stratification factors, enrollment ctDNA(+) was associated with shorter PFS (HR, 2.51 [95% CI, 1.73 to 3.66]; P < .0001), and similarly, shorter DSS (HR, 2.69 [95% CI, 1.43 to 5.06]; P = .002) and OS (HR, 2.05 [95% CI, 1.20 to 3.67]; P = .009; Figs 2A–2D; Data Supplement, Fig S16). The prognostic signal was similar across baskets (Data Supplement, Fig S17). Regardless of ctDNA, however, MDT + SOC was associated with relative PFS improvement: ctDNA(+): HR, 0.61; 95% CI, 0.38 to 0.98; P = .04; ctDNA(−): HR, 0.41; 95% CI, 0.22 to 0.76; P = .005; interaction P = .6. Although the magnitude and certainty of benefit appeared larger in the ctDNA(−) versus ctDNA(+) subgroup, no interactions were observed overall or within baskets.
FIG 2.
Association between ctDNA status and outcomes. (A and B) ctDNA(+) was associated with shorter PFS (HR, 2.51 [95% CI, 1.73 to 3.66]; P < .0001) and (C and D) OS (HR, 2.05 [95% CI, 1.20 to 3.67]; P = .009). Models were adjusted for the random assignment arm, basket, and the common random assignment stratification factors (number of metastases and number of prior lines of systemic therapy). (E) Clearance of ctDNA at 3-month follow-up was associated with improved OS (HR, 0.25 [95% CI, 0.08 to 0.64]; P = .003). (F) ctDNA tumor fraction response following MDT + SOC versus SOC. ctDNA, circulating tumor DNA; HR, hazard ratio; MDT, metastasis-directed therapy; OS, overall survival; SOC, standard of care; PFS, progression-free survival.
ctDNA(+) 3 months after enrollment (available in 186 patients, after excluding 13 patients with early PFS events) was also associated with PFS landmarked to 3 months (HR, 1.94 [95% CI, 1.25 to 2.99]; P = .003). Similarly, 3 month ctDNA(+) was associated with DSS (HR, 3.66 [95% CI, 2.04 to 6.57]; P < .0001) and OS (HR, 2.59 [95% CI, 1.46 to 4.72]; P = .001).
Differences in ctDNA clearance rate, defined as conversion of ctDNA from detectable to undetectable, were apparent without statistical significance between MDT + SOC (15/46, 33%) and SOC (10/44, 23%; odds ratio, 1.65 [95% CI, 0.65 to 4.20]; P = .3; Data Supplement, Fig S18; Fig 2E). Clearance of ctDNA was associated with longer landmarked OS (HR, 0.25 [95% CI, 0.08 to 0.64]; P = .003; Fig 2F). At progression, ctDNA(+) increased to 79% (65/82) of patients from 43% at 3-month follow-up (81/188) alongside an increase in methylated ctDNA tumor fraction (Data Supplement, Figs S18 and S19).
Immune Profiling
Compared with matched baseline peripheral blood samples, immune profiling revealed induction of immune subsets after MDT + SOC but not SOC, including CD8+ T cells with markers of proliferation (ie, Ki67+) and activation (eg, CD25+, PD1+, and LAG3+; Fig 3A). Moreover, CD8+ PD1+ Ki67+ T cells, which may represent a tumor-reactive phenotype, were higher after MDT + SOC arm but not SOC (Figs 3B and 3C).18–21 Induction of CD8+ PD1+ Ki67+ at the end of MDT correlated with more favorable OS (Fig 3D). Similarly, MDT + SOC was associated with an increased secretion of T helper 1 and CD8+ polarizing cytokines as well as TCR expansion and contraction, the end products of effective immunostimulation (Figs 3A, 3E–3F).12,22,23 Among MDT + SOC treated patients, compared with baskets without PFS superiority, baskets with PFS superiority showed evidence of greater immune activity after MDT + SOC, including CD8+ PD1+ Ki67+ T-cell induction, cytokine secretion, and TCR expansion (Fig 4). Taken together, these findings raise the hypothesis that differences in the observed efficacy between baskets might be related to underlying differences in immune stimulation.
FIG 3.
MDT + SOC is associated with systemic immune activation versus SOC. (A) Median fold change between enrollment and matched 3-month follow-up for each arm for significant changes. Gray squares indicate no significant difference by Wilcoxon signed-rank test. (B) Proliferating T cells with potential anti-tumor activity (CD8+ PD1+ Ki67+) are increased after MDT + SOC but not after SOC per Wilcoxon signed-rank tests. Lines show median and IQR. (C) Multivariable linear mixed-effect models, adjusted for fixed effects of basket, prior lines of systemic therapy, and number of metastases with individuals as random effects, identify an interaction between MDT + SOC and induction of proliferating T cells (CD8+ PD1+ Ki67+). Estimated marginal means with 95% CI are shown, which represent the model-calculated average values for each group after adjustment. (D) Levels of proliferating T cells (CD8+ PD1+ Ki67+) at the end of MDT are associated with OS. Mean log hazard rate with shaded regions representing the 95% CI is plotted versus biomarker values. (E) TCR expansion and contraction shown per patient; # indicates expansion of >150 clones, and * indicates no observed expansion or contraction. (F) MDT + SOC is associated with TCR expansion, TCR contraction, and repertoire reshaping measured by Morisita index at 3-month follow-up. Lines show median and IQR. P for expansion and contraction were estimated by negative binomial models and for Morisita index by analysis of covariance. MDT, metastasis-directed therapy; OS, overall survival; SOC, standard of care; TCR, T-cell receptor.
FIG 4.
Immune responses are basket-specific and related to MDT benefit. (A) CD8+ PD1+ Ki67+ T cells are increased after MDT + SOC among patients in the baskets demonstrating PFS benefit (prostate and pancreas) compared with the baskets without PFS benefit (kidney and breast) by Mann-Whitney U. Lines show median and IQR. (B) Multivariable mixed-effect models, adjusted for fixed effects of basket, metastasis number, and prior lines of systemic therapy and random effects within patients, identify an interaction between MDT + SOC and induction of CD8+ PD1+ Ki67+ T cells in the baskets with PFS benefit, but not in the baskets without PFS benefit. Estimated marginal means with 95% CI are shown, which represent the model-calculated average values for each group. (C) TCR expansion and contraction compared between arms within baskets by Mann-Whitney U. Each bar represents one patient. # indicates expansion of >150 clones. *Indicates no observed expansion or contraction. (D) TCR expansion at the end of MDT appears greater among the baskets showing PFS benefit than among the baskets without PFS benefit. Estimated marginal means are obtained from a negative binomial model. (E) An interaction between MDT + SOC and induction of IL-15 is seen among the baskets with PFS benefit but not among the baskets without PFS benefit. Estimated marginal means with 95% CI are from linear mixed-effect models. IL, interleukin; MDT, metastasis-directed therapy; SOC, standard of care; PFS, progression-free survival; TCR, T-cell receptor.
DISCUSSION
The addition of MDT to SOC improved PFS, meeting the primary end point. To our knowledge, as the largest randomized trial to date investigating MDT for oligometastatic disease, EXTEND both affirms and advances the findings of SABR-COMET and CORE—that MDT improves PFS— using a larger sample size, balancing of histologies between arms, and incorporating up-to-date systemic therapy.2,3,24 Pancreatic and prostate cancer showed greatest promise, and we have initiated the phase III EXPAND trial (ClinicalTrials.gov identifier: NCT06593431) in pancreatic cancer. Multiple independent phase III efforts are underway in prostate cancer. The other histology basket raises the level of evidence supporting ongoing investigations of MDT in other sites such as head and neck and gynecologic malignancy. Translational analyses suggest that future research should leverage biomarkers for enhancing the therapeutic window.
To our knowledge, EXTEND is the first randomized trial for oligometastatic kidney cancer.25 In hindsight, control arm outcomes considerably exceeded estimates used for trial powering, rendering interpretations more inconclusive. Trials designed and powered with novel targeted therapy and immunotherapy agents in mind are needed for more definitive investigation.26,27 Alternatively, for select patients, MDT in lieu of systemic therapy may represent a promising de-escalation strategy, and biomarker-driven stratification may help to facilitate which patients may be good candidates for MDT monotherapy.28–31 To test these hypotheses further, we have initiated the phase II randomized ASTROs trial (ClinicalTrials.gov identifier: NCT06004336) comparing MDT followed by pembrolizumab or surveillance. Finally, whether MDT is beneficial when directed at metastases progressing on systemic therapy remains an open question and is being tested in our EXTEND oligoprogression (EXTEND-OP) trial (ClinicalTrials.gov identifier: NCT06367972) which includes a large renal cell carcinoma basket.
Counting radiologic lesions to define oligometastatic disease may be suboptimal for patient selection and understanding the burden of micrometastatic disease.32,33 Building on prior studies, we found strong prognostic associations between ctDNA and multiple outcomes independent of clinical factors and ctDNA time point.34,35 Patients with ctDNA(−), marking a low burden of micrometastatic disease, might achieve significant clinical benefit with consolidative MDT in terms of both disease control and systemic therapy de-escalation. Alternatively, ctDNA(+) may indicate subclinical resistance and potential benefit from cytoreduction by MDT and/or systemic therapy switch. Clearance of ctDNA with MDT + SOC may rescue prognosis, and dynamic ctDNA assessment might represent a new intermediate surrogate end point. Validation studies to optimize treatment (de)-escalation are in planning. Finally, immune responses to MDT + SOC appear to be histology-specific and additionally associated with MDT efficacy. Further work is needed to test the hypothesis that MDT-induced immune responses are mediate systemic disease control and therapeutic implications.
EXTEND was designed as a signal-finding study, emphasizing efficiency and pragmatism, and must be interpreted accordingly. Given the growth of clinical data since the initiation of EXTEND, future trials should carefully consider expected control arm performance and anticipate adaptation to novel systemic therapies during enrollment. Secondary end point effect estimations may have been obscured by crossover and heterogeneous postprogression salvage. Differential protocols for surveilling disease between baskets were used to emulate routine clinical practice patterns and in part for practical reasons (eg, serial imaging is typically not reimbursable in the United States in prostate cancer). Although modality differences in follow-up could have led to potential differences in PFS detection rates, prespecified and sensitivity analyses suggest only a limited effect of this potential bias. Patient-reported outcome response rates were poor, in part because the COVID-19 pandemic complicated follow-up and communications, although data may be missing not at random because of perceived disappointment in the random assignment. Translational assays should be interpreted as exploratory given the lack of prespecification and multiplicity control. Although landmarked, post-random assignment analyses of covariates are affected by immortal time and selection bias and should be interpreted cautiously.
The EXTEND trial provides randomized evidence elucidating the role of MDT for oligometastatic disease in a histology-specific context. These findings should inform future trials and translational efforts; for certain disease sites, they caution against the routine use of MDT in clinical practice outside of a clinical trial. Basket designs seem to be well suited for future MDT trial concepts in oligometastatic and oligoprogressive disease.
Supplementary Material
CONTEXT.
Key Objective
Does the combination of metastasis-directed therapy (MDT) and standard-of-care (SOC) systemic therapy improve progression-free survival (PFS) compared with systemic therapy alone among patients with oligometastatic disease?
Knowledge Generated
In this phase II randomized trial of 334 patients, MDT + SOC significantly improved PFS as compared with SOC, particularly among patients with prostate cancer or pancreatic cancer. Translational insights indicate the potential for refining the definition and management of oligometastatic disease by incorporating novel molecular biomarkers including circulating tumor DNA and immune measures.
Relevance (C. Chung)
As systemic therapy advances continue to evolve the natural history of metastatic disease for the various tumor histologies, continued investigation and optimization of multimodal therapy, such as MDT, can benefit patient outcomes.*
*Relevance section written by JCO Associate Editor Caroline Chung, MD, MSc, FRCPC.
ACKNOWLEDGMENT
We would like to acknowledge Christine Wogan, MS, ELS, of The University of Texas MD Anderson Cancer Center’s Division of Radiation Oncology for her editorial contributions, for which she received no compensation beyond her salary. We would like to thank Guardant Health for their support and guidance.
SUPPORT
Supported by grant RP180140 from the CPRIT (CT); by the TLC Foundation (CT); by grant P30 CA016672 from National Cancer Institute (MD Anderson ORION core); and by the Translational Molecular Pathology-Immunoprofiling Moon Shots Platform at the Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center.
Footnotes
PRIOR PRESENTATION
Presented in part at the American Society for Radiation Oncology Annual Meeting, San Francisco, CA, September 30, 2025; and the European Society of Radiotherapy and Oncology Annual Meeting, Stockholm, Sweden, May 16, 2026.
CLINICAL TRIAL INFORMATION
NCT03599765 (EXTEND)
AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
Disclosures provided by the authors are available with this article at DOI https://doi.org/10.1200/JCO-25-02856.
AUTHORS’ DISCLOSURES OF POTENTIAL CONFLICTS OF INTEREST
Addition of Metastasis-Directed Therapy to Standard of Care for Oligometastatic Disease: Primary Aggregated Analysis of All Baskets from the Phase II Randomized EXTEND Trial
The following represents disclosure information provided by authors of this manuscript. All relationships are considered compensated unless otherwise noted. Relationships are self-held unless noted. I = Immediate Family Member, Inst = My Institution. Relationships may not relate to the subject matter of this manuscript. For more information about ASCO’s conflict of interest policy, please refer to www.asco.org/rwc or ascopubs.org/jco/authors/author-center.
Open Payments is a public database containing information reported by companies about payments made to US-licensed physicians (Open Payments).
Alexander D. Sherry
Employment: MD Anderson Cancer Center, Mayo Clinic Cancer Center
Honoraria: Sermo
Cara Haymaker
Stock and Other Ownership Interests: Briacell
Consulting or Advisory Role: Regeneron
Research Funding: Iovance Biotherapeutics (Inst), Sanofi (Inst), BTG (Inst), Avenge Bio (Inst), Obsidian Therapeutics (Inst), KSQ Therapeutics (Inst), Yingli Pharma (Inst), Genentech (Inst), EMD Serono/Merck (Inst), ARTIDIS (Inst), Nanobiotix (Inst), AstraZeneca/MedImmune (Inst), Novartis (Inst), Summit Therapeutics (Inst), Takeda (Inst), Theolytics (Inst)
Patents, Royalties, Other Intellectual Property: Patent Appl No. 62/977, 672 (Inst)
Suyu Liu
Uncompensated Relationships: Polaris Consulting, LLC
Aaron Seo
Honoraria: Sermo
Kieko Hara
Research Funding: NanoString Technologies
Jay Reddy
Employment: MD Anderson Cancer Center
Stock and Other Ownership Interests: LatentSafe
Stephen G. Chun
Leadership: NRG Oncology (Inst)
Honoraria: AstraZeneca, Curio Science, Novocure
Consulting or Advisory Role: AstraZeneca, Novocure, Amgen
Research Funding: Nektar, National Cancer Institute
Travel, Accommodations, Expenses: AstraZeneca, Novocure, Curio Science
Gary Walker
Employment: Banner MD Anderson Cancer Centet
Shubham Pant
Stock and Other Ownership Interests: Teleprian, Oncomed LLC
Consulting or Advisory Role: Ipsen, Novartis, Janssen, Boehringer Ingelheim, AskGene Pharma, BPGbio, Jazz Pharmaceuticals, AstraZeneca, US WorldMeds, Nihon Medi-Physics, Alligator Bioscience, Revolution Medicines, Arcus Biosciences, Pfizer, Merck, Immuneering, EMD Serono, BMS GmbH & Co KG, Daiichi Sankyo
Research Funding: Mirati Therapeutics (Inst), Lilly (Inst), Xencor (Inst), Novartis (Inst), Rgenix (Inst), Bristol Myers Squibb (Inst), Astellas Pharma (Inst), Purple Biotech (Inst), 4D Pharma (Inst), Boehringer Ingelheim (Inst), NGM Biopharmaceuticals (Inst), Janssen (Inst), Arcus Biosciences (Inst), Elicio Therapeutics (Inst), bionte (Inst), Ipsen (Inst), Zymeworks (Inst), Pfizer (Inst), ImmunoMET (Inst), Immuneering (Inst), Amal Therapeutics (Inst), BMS GmbH & Co. KG (Inst)
Dan Zhao
Consulting or Advisory Role: Ipsen, Revolution Medicines
Research Funding: CARsgen Therapeutics (Inst), Mirati Therapeutics (Inst), TriSalus Life Sciences (Inst), Phanes Therapeutics (Inst), Affini-T Therapeutics (Inst)
Travel, Accommodations, Expenses: Dava oncology
Other Relationship: CAHON, OncLive Peer Exchange Filming
Craig A. Kovitz
Honoraria: Dendreon
Consulting or Advisory Role: Dendreon
Chul S. Ha
Research Funding: Bayer (Inst)
Benjamin D. Smith
Research Funding: Artidis
Patents, Royalties, Other Intellectual Property: Through my employer, I have an equity interest in Oncora Medical as part of a partnership agreement (Inst)
Open Payments Link: https://openpaymentsdata.cms.gov/physician/730600
Daniel Gomez
Honoraria: Varian Medical Systems, AstraZeneca
Consulting or Advisory Role: Johnson & Johnson/Janssen, Regeneron
Research Funding: AstraZeneca
Travel, Accommodations, Expenses: Johnson & Johnson/Janssen
Lorenzo Cohen
Honoraria: Astellas Pharma
Consulting or Advisory Role: ReHeva Biosciences, Complement 1
Patents, Royalties, Other Intellectual Property: Book entitled: Anticancer Living: Transform Your Life and Health with the Mix of Six, Book entitled: The Principles and Practice of Yoga in Health Care
Alexandre Reuben
Consulting or Advisory Role: Adaptive Biotechnologies
Nizar Tannir
Stock and Other Ownership Interests: Amgen, Johnson & Johnson/Janssen, Vanguard Health Care, Spdr S&P Pharmaceuticals ETF, Abbvie, Gilead Sciences, Pfizer, Coherus Biosciences, ImmunityBio, ABSCI, Allogene Therapeutics, Cabaletta Bio, Moderna Therapeutics, Arcus Biosciences, Summit Therapeutics
Honoraria: Bristol Myers Squibb, Eisai, Merck Sharp & Dohme, Oncorena, Ipsen, Nektar, Exelixis
Research Funding: Bristol Myers Squibb (Inst), Nektar (Inst), Novartis (Inst), Calithera Biosciences (Inst), Arrowhead Pharmaceuticals Inc (Inst), Oncorena (Inst), Pfizer (Inst)
Paul G. Corn
Research Funding: Janssen Oncology (Inst)
Phuoc T. Tran
Honoraria: Reflexion Medical
Consulting or Advisory Role: Astellas Pharma, Regeneron, GenomeDx, Reflexion Medical, Dendreon, Reflexion Medical, Noxopharm, Janssen, Myovant Sciences, AstraZeneca, Bayer Health, Lantheus Medical Imaging, Novartis, Pfizer
Research Funding: Astellas Pharma (Inst), Reflexion Medical (Inst), Bayer Health (Inst)
Patents, Royalties, Other Intellectual Property: Compounds and Methods of Use in Ablative Radiotherapy. Patent filed March 9, 2012. PCT/US2012/028475. PCT/WO/2012/122471
Travel, Accommodations, Expenses: Reflexion Medical
Bilal A. Siddiqui
Honoraria: Cancer Expert Now, Curio Science, Cardinal Health, DAVA Pharmaceuticals
Consulting or Advisory Role: Merck, Pfizer, Amgen, Johnson and Johnson, Survivornet, Bayer, Astellas Pharma
Research Funding: Regeneron (Inst), Amgen (Inst), Conquer Cancer, the ASCO Foundation, Prostate Cancer Foundation, Cancer Research Institute, Johnson & Johnson/Janssen (Inst)
Travel, Accommodations, Expenses: Merck, Curio Science, Cardinal Health
Sumit K. Subudhi
Stock and Other Ownership Interests: Apricity Health
Honoraria: Arcus Biosciences, Bristol Myers Squibb, Dendreon, Hervolution, Johnson & Johnson, Merck, Novartis
Consulting or Advisory Role: Pfizer, AdvanCell, Apricity Health, Arcus Biosciences, Baird, Boxer Capital, Breaking Data, Bristol Myers Squibb, DAVA Oncology, Dendreon, Hervolution, Johnson & Johnson, Kahr Medical Ltd, Kiniksa, Macrogenics, Merck, NoeticInsight, Novartis, OncLive (owned by Intellisphere LLC), Pfizer, Portage Biotech, Regeneron, Rondo Therapeutics, SurvivorNet, Telix Pharmaceuticals, Clinical Comms Group, Third Bridge, Vicero, Vir Biotechnology Inc
Research Funding: Bristol Myers Squibb (Inst), Regeneron (Inst), Amgen (Inst), Arcus Biosciences (Inst), Macrogenics (Inst), Tarus Therapeutics (Inst), AstraZeneca, Johnson & Johnson
Pavlos Msaouel
Honoraria: Exelixis, Mirati Therapeutics, Pfizer
Consulting or Advisory Role: Axiom Healthcare Strategies
Research Funding: Mirati Therapeutics (Inst), Takeda (Inst), Bristol Myers Squibb (Inst), Gateway for Cancer Research (Inst), Summit Therapeutics
Ethan B. Ludmir
Employment: Alaunos Therapeutics (I)
Honoraria: Nanobiotix
Consulting or Advisory Role: Xerient
Chad Tang
Employment: MD Anderson Cancer Center
Consulting or Advisory Role: Boston Scientific, Telix Pharmaceuticals, MOLLI Surgical, Elekta
Research Funding: Noxopharm (Inst), Myriad Genetics (Inst)
Patents, Royalties, Other Intellectual Property: I have a patent on the utilization of a monoclonal antibody and we license this for use. We receive royalties <$1,000 per year on this license
Travel, Accommodations, Expenses: Vision RT
Other Relationship: Wolters Kluwer, Osler Institute
No other potential conflicts of interest were reported.
DATA SHARING STATEMENT
A data sharing statement provided by the authors is available with this article at DOI https://doi.org/10.1200/JCO-25-02856.
Deidentified patient-level data and all study-related documents can be made available with appropriate approval by the investigator team and research administrative offices. The study protocol is provided in the Data Supplement. Requests can be made to the corresponding author (C. Tang) after full manuscript publication. Data sharing will be subject to appropriate data transfer agreements.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
A data sharing statement provided by the authors is available with this article at DOI https://doi.org/10.1200/JCO-25-02856.
Deidentified patient-level data and all study-related documents can be made available with appropriate approval by the investigator team and research administrative offices. The study protocol is provided in the Data Supplement. Requests can be made to the corresponding author (C. Tang) after full manuscript publication. Data sharing will be subject to appropriate data transfer agreements.