Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC

Abstract

Background:

Oligoprogressive disease is recognized as the overall umbrella term; however, a small number of progressions on imaging can represent different clinical scenarios. This study aims to explore the optimal treatment strategy after immunotherapy (IO) resistance in advanced non-small-cell lung cancer (NSCLC), especially in personalized therapies for patients with different oligoprogressive patterns.

Methods:

Based on European Society for Radiotherapy and Oncology/European Organization for Research and Treatment of Cancer consensus, metastatic NSCLC patients with cancer progression after IO resistance were divided into four patterns, repeat oligoprogression (REO, oligoprogression with a history of oligometastatic disease), induced oligoprogression (INO, oligoprogression with a history of polymetastatic disease), de-novo polyprogression (DNP, polyprogression with a history of oligometastatic disease), and repeat polyprogression (REP, polyprogression with a history of polymetastatic disease). Patients with advanced NSCLC who received programmed cell death-1/programmed cell death ligand-1 inhibitors between January 2016 and July 2021 at Shanghai Chest Hospital were identified. The progression patterns and next-line progression-free survival (nPFS), overall survival (OS) were investigated stratified by treatment strategies. nPFS and OS were calculated using the Kaplan–Meier method.

Results:

A total of 500 metastatic NSCLC patients were included. Among 401 patients developed progression, 36.2% (145/401) developed oligoprogression and 63.8% (256/401) developed polyprogression. Specifically, 26.9% (108/401) patients had REO, 9.2% (37/401) patients had INO, 27.4% (110/401) patients had DNP, and 36.4% (146/401) patients had REP, respectively. The patients with REO who received local ablative therapy (LAT) had significant longer median nPFS and OS compared with no LAT group (6.8 versus 3.3 months; p = 0.0135; OS, not reached versus 24.5 months; p = 0.0337). By contrast, there were no nPFS and OS differences in INO patients who received LAT compared with no LAT group (nPFS, 3.6 versus 5.3 months; p = 0.3540; OS, 36.6 versus 45.4 months; p = 0.8659). But in INO patients, there were significant longer median nPFS and OS using IO maintenance by contrast with IO halt treatment (nPFS, 6.1 versus 4.1 months; p = 0.0264; OS, 45.4 versus 32.3 months; p = 0.0348).

Conclusions:

LAT (radiation or surgery) is more important for patients with REO while IO maintenance plays a more dominant role in patients with INO.

Keywords

immunotherapy local ablative therapy non-small-cell lung cancer oligoprogression progression pattern

Introduction

Despite the great success of targeted therapies in patients with non-small-cell lung cancer (NSCLC), most NSCLC patients do not harbor a currently targetable driver alteration.^1–4 Immunotherapy (IO), with or without chemotherapy, has been the standard treatment in the first-line setting for patients without EGFR mutation, BRAF V600E mutation, RET, ALK, or ROS fusion patients.^5–8 IO is admitted as a second-line treatment option after platinum-based chemotherapy.⁹ Moreover, clinical trials provided strong evidence of programmed cell death ligand-1 (PD-(L)1) blockade and chemotherapy plus anti-angiogenesis as a new therapeutic strategy in EGFR-TKI-resistant patients.^10,11 Despite these triumphs, the majority of patients eventually failed to respond to immune checkpoint inhibitors (ICIs) therapy due to the evolution of primary or secondary resistance. Approximately, only 20–48% of patients with metastatic disease responded to ICIs^6,12,13 while the majority of them would eventually progress.¹⁴

Metastatic lung cancer had traditionally been considered incurable, whose treatment focused on a systemic therapy to extend the life of patients. It was not until 1995 that Hellman and Weichselbaum first described the oligometastatic state as an intermediate stage between locoregionally confined disease and widespread distant metastases based on the spectrum theory of cancer spread.¹⁵ Although it was not well characterized in the historical literature, recent data suggested that oligometastatic progression after the failure of ICI-based therapy was common (12.9–55.3%)^16–19 among NSCLC patients.

However, two very different clinical scenarios are tumors early in the chain of oligoprogression with metastases limited in number and location while another group of patients who had widespread metastases that were mostly eradicated by systemic agents.¹⁵ Despite being under the umbrella term of oligoprogression that reminds similar features on imaging, these two scenarios differ remarkably from a clinical perspective which may lead to contrasting outcomes and require different treatment strategies. Therefore, in 2020, the European Society for Radiotherapy and Oncology (ESTRO) and European Organization for Research and Treatment of Cancer (EORTC) OligoCare project developed a comprehensive system to meet the need for better characterization and classification of the different states of oligoprogression.²⁰

Though being mostly retrospective, previous studies^16,21–25 showed that continuation IO associated with local ablative therapy (LAT) after progression disease appeared to be a safe therapeutic option which could promise long-term survival for advanced NSCLC patients who oligoprogressed on IO, yet not all oligoprogressive patients upon ICIs resistance could benefit from LAT. The heart of the problem is that oligoprogressive disease is still recognized as an entity, regardless of a wide range of ways to classify it. A subsequent question has to be raised: how should the patients be classified?

Our main purpose is to examine the validity of oligoprogressive disease classification established by ESTRO/EORTC as well as the current therapeutic approaches based on the patterns of disease progression. This study also aims at exploring effective treatment strategies based on these different patterns.¹⁵

Materials and methods

Definition of progression patterns

According to the ESTRO/EORTC consensus, oligometastatic disease (a maximum of five metastases and three organs²⁶) was classified as nine distinct states, which were associated with different prognoses and might require different treatment strategies.²⁰ To make it clear, oligoprogression was defined as patients with progressive oligometastatic disease after IO treatment. A history of oligometastatic/polymetastatic disease before diagnosis of oligoprogression was used as the criterion to differentiate between two oligoprogression subclassifications. Two polyprogression (>5 metastases or >3 organs) patterns were also defined in our study (Figure 1).

(1) Repeat oligoprogression (REO): diagnosis of oligoprogression with a history of oligometastatic disease;

2) Induced oligoprogression (INO): diagnosis of oligoprogression with a history of polymetastatic disease;

3) De-novo polyprogression (DNP): diagnosis of polyprogression with a history of oligometastatic disease;

4) Repeat polyprogression (REP): diagnosis of polyprogression with a history of polymetastatic disease.

Figure 1.

Illustration of oligoprogression and polyprogression classification system.

Patients

A total of 821 patients with NSCLC receiving programmed cell death-1 (PD-1)/ PD-L1 IO were included from January 2016 to July 2021 at Shanghai Chest Hospital. They were chosen based on the following criteria: (1) diagnosis of stage IV primary NSCLC based on the 8th edition of TNM staging system; (2) administration of IO monotherapy/IO combination based on PD-1/PD-L1 inhibitors; (3) without EGFR mutation, ALK rearrangements, ROS1 rearrangements, RET rearrangements, or MET exon 14 mutations; (4) Eastern Cooperative Oncology Group performance status (ECOG PS) ⩽ 2; (5) at least one measurable lesion as defined by Response Evaluation Criteria in Solid Tumors (RECIST) 1.1²⁷; (6) completed tumor response evaluation for IO at least once; (7)thoracic computed tomography (CT), brain magnetic resonance imaging (MRI)/CT, and bone scan as well as ultrasound examination or CT of the abdomen and/or positron emission tomography (PET)/CT should be performed in all patients at baseline and IO resistance. Regular follow-up should include thoracic CT and abdominal CT/ultrasound. Whether brain MRI/CT, bone scan, or PET-CT was performed was dependent on the decision of the clinical physician. All patients were in follow-up.

Clinical data were retrieved from the electronic medical records of Shanghai Chest Hospital. Data acquisition was in line with relevant legislation and institutional review board guidelines.

Follow-up and survival

The last follow-up date was 1 January 2022, with regular follow-up every 3 months.

Overall survival (OS) was defined as the time from initiation of IO for advanced NSCLC to death from any cause. Progression-free survival (PFS) was defined as the time from the first cycle of IO to the first disease progression. Before the last follow-up date (1 January 2022), 99 patients without event were censored and 401 patients developed disease progression according to RECIST v1.1 criteria were included in the main analysis (Figure 2). For patients with IO halt, nPFS was defined as the time from the start of next-line treatment(withdraw IO and convert to other strategies) after IO resistance to objective tumor progression or death from any cause. For patients with IO maintenance, nPFS was defined as the time from the start of IO rechallenge after IO first progression to IO second progression or death from any cause.

Figure 2.

Flow diagram of the patients enrolled in the study.

Statistical analysis

The PFS and OS were calculated using the Kaplan–Meier method, and between treatment, differences were assessed by the stratified log-rank test. Those patients who were alive or without disease progression on the last follow-up date (1 January 2022) were censored. Hazard ratio (HR) and 95% confidence interval (CI) were estimated based on a stratified Cox model. A p value of less than 0.05 was regarded as statistically significant.

Differences in the categorical variables were evaluated using chi-square (χ²) test or Fisher’s exact test, as appropriate. Association between clinical and biological variables and progression patterns were assessed with univariate analysis and multivariate analysis. All reliable variables associated with oligoprogression were entered into a multivariable model using forward stepwise binary logistic regression analysis. To maximize statistical power and minimize bias that might occur in patients with PD-L1 expressing missing data excluded from analyses, multivariate multiple imputations to impute missing were used based on five replications in SPSS.²⁸

Statistical analyses were performed with SPSS version 26.0 while most figures were created with GraphPad Prism version 8.0 and eBioRender.

Results

Patient characteristics and outcomes of IO

Overall, 821 NSCLC patients were treated with anti-PD-1/PD-L1 antibody therapy during the study period, 500 of them were following the inclusion criteria. Beyond IO progression, the remaining 401 patients were included in the main analysis (Figure 2). The median follow-up duration was 28.3 months (range, 5.2–66.3 months).

Patient demographics and clinical characteristics in the overall study population were summarized in Supplemental Table 1. The median age was 63 years. Most patients were under 65 years (56.0%, 280/500), men (83.8%, 419/500), had an ECOG PS of 0–1 (98.0%, 490/500), with a history of smoking (66.8%, 334/500), and adenocarcinoma histology (58.6%, 293/500). The PD-L1 Tumor Proportion Score was categorized as <1%, 1–49%, ⩾50%, and unknown in 17.8% (89/500), 17.6% (88/500), 14.4% (72/500), and 50.2% (251/500) of patients, respectively. The majority of patients (54.4%, 272/500) were diagnosed with polymetastatic disease at baseline.

Among all eligible patients, 58.6% (293/500) patients received IO monotherapy, and 41.4% (207/500) received IO combination therapy. A total of 46.6% (233/500) patients received IO as first-line treatment, 40.0% (200/500) and 13.4% (67/500) received second-line, and third-line or later treatment. In total, 36.6% (183/500) patients achieved partial response (PR) or complete response (CR), 43.6% (218/500) patients had stable disease (SD), and 19.8% (99/500) patients had progressive disease (PD).

In the overall population, the estimated median PFS (mPFS), and median OS (mOS) of IO were 7.4 months (95% CI, 6.3–8.5 months) and 25.6 months (95% CI, 23.7–27.6 months), respectively (Figure 3(a) and (b)).

Figure 3.

Kaplan–Meier curves of PFS and OS among metastatic NSCLC patients receiving IO therapy. The IO PFS (a) and OS (b) among all eligible NSCLC patients without driver mutation. The immunotherapy PFS (c) and OS (d) in all patients developing progression stratified by different progression patterns.

Progression patterns after ICIs failure

Before cutoff date (1 January 2022), 401 patients developed disease progression. The progression patterns of 401 patients who experienced disease progression beyond IO are shown in Figure 4(a). Among them, 36.2% (145/401) of patients developed oligoprogression and 63.8% (256/401) developed polyprogression. Specifically, 26.9% (108/401) patients had REO, 9.2% (37/401) patients had INO, 27.4% (110/401) patients had DNP, and 36.4% (146/401) patients had REP. The demographics and clinical characteristics of patients with different progression patterns beyond IO resistance are summarized in Supplemental Table 1.

Figure 4.

Progressive patterns and organs after IO resistance. (a) The proportion of oligoprogression (subclassified as REO and INO) and polyprogression (subclassified as DNP and REP) in overall metastatic NSCLC patients. (b) The organ progression rates of overall metastatic NSCLC patients beyond IO resistance.

The progressive rates of different organs in all IO-resistant patients are shown in Figure 4(b). Primary lesion (59.1%, 237/401), contralateral lung (28.9%, 116/401), and thoracic lymph node (24.9%, 100/401) were the most common sites of progression beyond IO treatment.

Survival analysis of different progression patterns

Upon IO failure, among four progression patterns of patients, those who were classified as INO had significantly better mPFS than those classified as REO, DNP, or REP [mPFS, 11.1 months (95% CI, 3.1–19.2) versus 7.4 months (95% CI, 6.1–8.8) versus 5.1 months (95% CI, 4.0–6.2) versus 2.9 months (95% CI, 1.8–4.0); p < 0.0001] respectively (Figure 3(c)). Similarly, patients with INO showed superior mOS than other groups (mOS, 45.4 months [95% CI, 26.5–64.2] versus 27.2 months [95% CI, 21.4–32.9] versus 23.2 months [95% CI, 18.7–27.7] versus 16.7 months [95% CI, 14.4–19.0]; p < 0.0001), respectively (Figure 3(d)). There was no difference in IO administration (monotherapy/combination) between four different progression patterns (χ² = 4.26; p = 0.2350; number of patients was shown in Supplemental Table 1).

Clinical factors associated with progression patterns

Univariate analysis revealed that progression patterns were associated with gender, ECOG PS, smoking history, histology, baseline metastatic status, lines of IO, best response, and tumor PD-L1 expression (Table 1).

Table 1.

Univariable and multivariable binary logistic regression analyses of patient characteristics and progression patterns.

	All progression patients (n = 401)		Univariate analysis		Multivariate analysis
	Oligoprogression (n = 145)	Polyprogression (n = 256)	OR (95% CI)	p Value	OR (95% CI)	p Value
Age
<65 years	90	144	1.27 (0.84–1.93)	0.2561
⩾65 years	55	112
Gender
Male	134	197	3.65 (1.85–7.20)	<0.0001	3.81 (1.46–9.99)	0.0064
Female	11	59
ECOG PS
0–1	145	247	1.59 (1.47–1.71)	0.0295	0.00 (0.00–NA)	0.9987
⩾2	0	9
Smoking status
Never	40	97	0.62 (0.40–0.97)	0.0366	1.01 (0.54–1.89)	0.9690
Current or former	105	159
Histology
LUAD	74	160	0.63 (0.41–0.94)	0.0252	1.11 (0.66–1.86)	0.6876
Others	71	96
Baseline metastatic status
Oligometastase	108	110	3.87 (2.48–6.06)	<0.0001	6.94 (3.78–12.75)	<0.0001
Polymetastase	37	146
Radiotherapy history
No	116	183	1.60 (0.98–2.60)	0.0599
Yes	29	73
Lines of IO therapy
1^st	75	92	1.91 (1.26–2.89)	0.0021	1.10 (0.63–1.93)	0.7350
⩾2^nd	70	164
Best response
CR or PR	81	42	6.45 (4.05–10.27)	<0.0001	11.68 (6.04–22.60)	<0.0001
SD or PD	64	214
IO drug
Anti-PD-1	128	219	1.27 (0.69–2.35)	0.4418
Anti-PD-L1	17	37
PD-L1 expression
<50%	45	91	0.52 (0.27–1.00)	0.0486	0.87 (0.32–2.37)	0.7718
⩾50%	24	25
NA	76	140
IO treatment
IO monotherapy	85	171	0.70 (0.46–1.07)	0.1016
IO combination	60	85

CR, complete response; ECOG PS, Eastern Cooperative Oncology Group performance status; IO, immunotherapy; LUAD, lung adenocarcinoma; NA, not available; OR, odds ratio; PD, disease progression; PD-L1, programmed cell death ligand-1; PR, partial response; SD, stable disease.

In multivariable analysis, oligoprogression was associated only with male gender [odds ratio (OR), 3.81; 95% CI, 1.46–9.99; p = 0.0064], higher proportion of baseline oligometastases (OR, 6.94; 95% CI, 3.78–12.75; p < 0.0001) and higher objective response rate (ORR; OR, 11.68; 95% CI, 6.04–22.60; p < 0.0001). There was no significant difference in other clinical characteristics between oligoprogression and polyprogression patients in multivariable analysis (Table 1).

Patients developing oligoprogression after IO failure

Next-line treatment strategies of different progressive patterns after IO in metastatic NSCLC patients are shown in Supplemental Table 2.

After IO treatment resistance, patients with REO had substantial survival advantages from LAT. The median nPFS was significantly prolonged (6.8 versus 3.3 months; HR, 0.48; 95% CI, 0.30–0.78; p = 0.0135) (Figure 5(a)), while mOS was not reached (not reached versus 24.5 months; HR, 0.39; 95% CI, 0.21–0.74; p = 0.0337) (Figure 5(b)). It is worth noticing that the survival benefits in the LAT group were not observed in the INO subgroup (nPFS, 3.6 versus 5.3 months; HR, 0.69; 95% CI, 0.28–1.69; p = 0.3540; OS, 36.6 versus 45.4 months; HR, 0.90; 95% CI, 0.26–3.06; p = 0.8659) (Figure 5(c) and (d)).

Figure 5.

Kaplan–Meier curves of the next-line PFS and OS among oligoprogression patients beyond IO resistance. The nPFS (a) and OS (b) among REO patients receiving LAT or not as next-line treatment; the nPFS (c) and OS (d) among INO patients receiving LAT or not as next-line treatment; The nPFS (e) and OS (f) among induced oligoprogression patients receiving IO maintenance versus IO halt after IO resistance.

In REO subgroup, most patients (12/17) maintained a next-line progression-free status for at least 5 months. In INO subgroup, only two of nine patients had responses lasting longer than 5 months after next-line LAT while most patients got PD quickly; notably, among these two patients, one had a long PFS of IO and continued ICI treatment after local therapy (Supplemental Figure 1).

For patients with INO, median nPFS favored the IO maintenance group compared to IO halt group (6.1 versus 4.1 months; HR, 0.45; 95% CI, 0.21–0.98; p = 0.0264) (Figure 5(e)). Similarly, OS trended in favor of the IO maintenance group (45.4 versus 32.3 months; HR, 0.35; 95% CI, 0.14–0.88; p = 0.0348) (Figure 5(f)). By contrast, IO maintenance offered no survival advantages in patients with REO subgroup (nPFS, 3.5 versus 4.4 months; HR, 0.83; 95% CI, 0.55–1.26; p = 0.3861; OS, 36.5 versus 24.5 months; HR, 0.60; 95% CI, 0.35–1.04, p = 0.0525) (Supplemental Figure 2).

Patients developing polyprogression after IO failure

Among patients in DNP subgroup, no benefits were obtained from either LAT or IO maintenance (LAT versus no LAT, nPFS, 2.0 versus 3.1 months; HR, 0.97; 95% CI, 0.56–1.66; p = 0.9003; OS, 18.5 versus 23.5 months; HR, 0.81; 95% CI, 0.43–1.51, p = 0.4509) (IO maintenance versus IO halt, nPFS, 3.2 versus 2.4 months; HR, 0.76; 95% CI, 0.51–1.12; p = 0.1520; OS, 21.6 versus 19.3 months; HR, 0.77; 95% CI, 0.49–1.22, p = 0.2699) (Supplemental Figure 3A–D).

Consistently, patients with REP could not benefit from either LAT or IO maintenance (LAT versus no LAT, nPFS, 2.3 versus 3.0 months; HR, 0.91; 95% CI, 0.55–1.53; p = 0.7195; OS, 21.5 versus 16.1 months; HR, 0.73; 95% CI, 0.43–1.22, p = 0.2767) (IO maintenance versus IO halt, nPFS, 3.3 versus 2.8 months; HR, 0.86; 95% CI, 0.61–1.20; p = 0.3689; OS, 17.1 versus 16.7 months; HR, 0.82; 95% CI, 0.56–1.19, p = 0.2921) (Supplemental Figure 4A–D).

Discussion

The advent and development of IO had undoubtedly contributed to the improved outcomes for patients with NSCLC. Nonetheless, it was unavoidable that the majority of patients eventually failed to respond to IO therapy due to the evolution of primary or secondary resistance, which had propelled us to search for alternative approaches.

Currently, the consensus on oligometastatic states had been reached in 2020,²⁰ while progression patterns after IO resistance were scarce in NSCLC patients. Furthermore, therapeutic strategies tailored for advanced NSCLC patients based on the types of progression were an unmet clinical need. Our study was a large-scale real-world research with the following three features. First, the sufficient population validated the decision tree constructed by ESTRO/EORTC, enabling us to analyze oligoprogression subgroups, which filled the gap in this field. Second, we were the first to propose that LAT conferred no significant improvement in OS in patients with INO, which was inconsistent with the previous studies regarding oligoprogressive patients as a whole.¹⁹ Lastly, the instructions of next-line treatment strategies based on progression patterns were offered.

In this article, we highlighted that LAT in the oligoprogressive state during IO could be considered in selected patients. Previous studies suggested using LAT for all patients with oligoprogression. For patients with INO, some researchers hypothesized that local treatment initially aimed to restore a status of overall sensitivity to systemic therapy through eradication of oligometastases with resistance to the current line of systemic therapy.²⁰ Consequently, this hypothesis might be inappropriate for the case of INO since the cure was not achieved in most patients. Notably, polymetastatic patients were converted into oligoprogressive patients in INO subgroup, which indicated excellent effectiveness of IO treatment and in that offered long-term superior survival benefits than other subgroups (Figure 3(c) and (d)). On the other hand, INO patients might develop unknown resistance mechanisms, which greatly weakened sequential LAT effect. At the same time, the meaningful benefit derived from IO maintenance after IO resistance (Figure 5(e) and (f)) indicated that systemic control played a dominant role for patients with INO when compared to local therapies. Our exploratory analysis focused on whether IO maintenance plus LAT outperformed LAT or IO maintenance: (1) LAT, (2) IO maintenance, and (3) LAT + IO maintenance. Regrettably, no significant benefit was observed in LAT + IO maintenance subgroup. However, the result was restricted by small population in each subgroup, so comparing IO alone versus IO plus LAT in REO and INO patients deserved further investigation in prospective clinical trials.

Although REO and DNP were both oligometastatic disease at the baseline of IO treatment, LAT for REO patients could be viewed as a supplement for IO, whereas unsuitable for DNP after IO resistance (Figure 5(a) and (b); Supplemental Figure 3A, B), which suggested that priority of LAT in oligometastatic patients might confer more significant survival benefits. Apart from complexed tumor micro-evolution, failure of LAT or IO maintenance in DNP and REP (Supplemental Figure 3A–D, Supplemental Figure 4A–D) might be attributed to the imbalance of rapid tumor growth and insufficient antitumor effect by therapies.

Possible explanations for different treatment strategy selection for four different progression patterns included the presence of underlying clonal heterogeneity and extrinsic selection pressure due to the use of IO.^29,30 To the best of our knowledge, mechanisms underlying IO resistance were still incompletely understood, especially in different progression patterns. Factors such as the cellular composition and heterogeneity of immunogenic and metabolic pathways within the tumor microenvironment (TME), as well as the mutational load driving tumor immunogenicity, all should be investigated in the future.

Rheinheimer et al. analyzed a group of 297 patients failing PD-1/PD-L1 inhibitors. Under IO monotherapy, oligoprogressive disease was more frequent (20% versus 10%), occurred later, affected fewer sites, and involved fewer lesions in the first compared to later lines.¹⁶ Similar observations were made by other researchers, for example, in a cohort of 148 patients under ICIs, 38 (26%) patients showed oligoprogression. Male sex, with a tendency of smoking history and lacking driver mutations, was significantly correlated with the risk of oligoprogression, which was partially consistent with our multivariate analysis.¹⁷ Then came the concern that further research was required to develop optimal approaches for the treatment of oligoprogressive patients. We collected current evidence on LAT in metastatic NSCLC patients who oligoprogressed on ICIs (Supplemental Table 3). In addition, there were several ongoing prospective clinical trials assessing the addition of LAT including radiotherapy to oligoprogressive IO-treated NSCLC patients (NCT04492969, NCT04549428, NCT03693014, NCT04405401). Overall, partial retrospective studies supported that IO and radiotherapy acted synergistically (Supplemental Table 3), which needed further large-scale prospective clinical trials. So far, no report had focused on the necessity of the distinction between progression patterns and subsequent therapies after IO resistance.

There were several limitations in our study. The nature of the retrospective study led to inevitable bias as well as reduced reliability. Oligoprogression groups were quite small, especially after a split in LAT yes or no. Baseline characteristics were not always well balanced and different treatment lines were included, influencing OS data. Selection bias might affect the results unavoidably despite we had tried our best to match the baseline patient demographics and lines of ICI therapy. LAT could be affected by clinical suggestion prescribed by doctors, patients’ choices, tolerability of patients, and limited feasibility in specific progression sites. For example, fewer patients in polyprogression group might choose LAT on account of worse tolerability than oligoprogression group. In addition, 53.4% patients in our study received IO on second line or further, which partly accounted for incomplete PD-L1 data. Although the robust data on clinicopathologic and progressive patterns allowed us to explore the outcomes of patients in our study thoroughly, the patients actually received treatment in all levels and under all conditions so the long-term outcomes might be affected by any unknown factors which could not be eradicated.

Taken together, this study showed that LAT might not be an appropriate choice for INO patients. This result evoked a hypothesis that overall deep response to systemic IO therapy might offer cancer cell-intrinsic variety or TME alterations or even neural regulation, which contributed to IO effectiveness and evolution of resistance mechanisms. In-depth tumor analysis including single-cell RNA-sequencing, whole-genome sequencing, multidimensional flow cytometry, or epigenetics might be implemented in the future to find out individualized treatment strategies.

Conclusions

LAT (radiation or surgery) is more important for patients with REO while IO maintenance plays a more dominant role in patients with INO (Figure 6).

Figure 6.

Graphical abstract of treatment strategies based on different oligoprogression patterns after IO resistance.

Supplemental Material

sj-jpg-1-tam-10.1177_17588359231156387 – Supplemental material for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC

Supplemental material, sj-jpg-1-tam-10.1177_17588359231156387 for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC by Wendi Xuzhang, Huayan Huang, Yongfeng Yu, Lan Shen, Ziming Li and Shun Lu in Therapeutic Advances in Medical Oncology

Supplemental Material

sj-jpg-2-tam-10.1177_17588359231156387 – Supplemental material for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC

Supplemental material, sj-jpg-2-tam-10.1177_17588359231156387 for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC by Wendi Xuzhang, Huayan Huang, Yongfeng Yu, Lan Shen, Ziming Li and Shun Lu in Therapeutic Advances in Medical Oncology

Supplemental Material

sj-jpg-3-tam-10.1177_17588359231156387 – Supplemental material for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC

Supplemental material, sj-jpg-3-tam-10.1177_17588359231156387 for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC by Wendi Xuzhang, Huayan Huang, Yongfeng Yu, Lan Shen, Ziming Li and Shun Lu in Therapeutic Advances in Medical Oncology

Supplemental Material

sj-jpg-4-tam-10.1177_17588359231156387 – Supplemental material for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC

Supplemental material, sj-jpg-4-tam-10.1177_17588359231156387 for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC by Wendi Xuzhang, Huayan Huang, Yongfeng Yu, Lan Shen, Ziming Li and Shun Lu in Therapeutic Advances in Medical Oncology

Supplemental Material

sj-jpg-5-tam-10.1177_17588359231156387 – Supplemental material for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC

Supplemental material, sj-jpg-5-tam-10.1177_17588359231156387 for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC by Wendi Xuzhang, Huayan Huang, Yongfeng Yu, Lan Shen, Ziming Li and Shun Lu in Therapeutic Advances in Medical Oncology

Supplemental Material

sj-jpg-6-tam-10.1177_17588359231156387 – Supplemental material for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC

Supplemental material, sj-jpg-6-tam-10.1177_17588359231156387 for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC by Wendi Xuzhang, Huayan Huang, Yongfeng Yu, Lan Shen, Ziming Li and Shun Lu in Therapeutic Advances in Medical Oncology

Supplemental Material

sj-jpg-7-tam-10.1177_17588359231156387 – Supplemental material for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC

Supplemental material, sj-jpg-7-tam-10.1177_17588359231156387 for Treatment strategies based on different oligoprogressive patterns after immunotherapy failure in metastatic NSCLC by Wendi Xuzhang, Huayan Huang, Yongfeng Yu, Lan Shen, Ziming Li and Shun Lu in Therapeutic Advances in Medical Oncology

Footnotes

Acknowledgements

Not applicable.

Declarations

ORCID iD

Shun Lu

Supplemental material

Supplemental material for this article is available online.

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