A narrative review of pathologic response in non-small cell lung cancer: challenges, implications, and future directions

Abstract

Background and Objective

The increasing use of neoadjuvant therapy in non-small cell lung cancer (NSCLC) has magnified the importance of pathologic response as a treatment endpoint. However, there are persistent challenges in its assessment and interpretation. This review aimed to synthesize current methods and challenges in evaluating pathologic response in patients with NSCLC, summarize available assessment techniques and biomarkers, and collate current data on pathologic response to neoadjuvant treatments and the association with survival outcomes.

Methods

We selected and reviewed articles proposing guidelines or approaches to the pathologic assessment of NSCLC, articles describing challenges in assessing pathologic response in NSCLC, and studies reporting pathologic response to neoadjuvant treatment and/or the association between pathologic response and survival outcomes. Data were extracted and summarized descriptively.

Key Content and Findings

In this review, we summarize methods for evaluating pathologic response in patients with resectable NSCLC and highlight current challenges, including variability in pathologic response assessment, the limited standardization of techniques and biomarkers, and the difficulty of interpreting pathologic response. We also review current clinical data on pathologic response to neoadjuvant chemotherapy, radiotherapy, immunotherapy, tyrosine kinase inhibitors (TKIs), and antiangiogenic therapies, and the association between pathologic response and survival outcomes. Finally, we review and discuss the selection of optimal treatment strategies for patients who achieve a pathologic response to neoadjuvant therapy.

Conclusions

Pathologic response is a valuable indicator of early response to treatment, but its current limitations necessitate a cautious and balanced approach in treatment decision-making for patients with early-stage resectable NSCLC, with consideration also given to other factors such as long-term survival and quality of life.

Introduction

Lung cancer is the leading cause of cancer-related mortality worldwide, accounting for 18.7% of all cancer-related deaths (1). Non-small cell lung cancer (NSCLC) is the most common type of lung cancer, comprising about 85% of all lung cancer cases (2). The 5-year survival rate for NSCLC varies widely depending on the stage at diagnosis, ranging from 67% for localized disease to 12% for distant metastatic disease (3). Historically, the standard of care for patients with stage II–IIIA operable NSCLC was surgical resection followed by adjuvant chemotherapy (4-7). However, meta-analyses of randomized trials showed that neoadjuvant chemotherapy was associated with similar survival benefits compared with adjuvant chemotherapy and could also be regarded as a standard option (8). More recently, trials have demonstrated improved patient outcomes with the use of immunotherapies and targeted therapies in the neoadjuvant and perioperative settings, changing the treatment paradigm for resectable NSCLC (9-11).

Pathologic response is commonly used to assess treatment-induced changes in resected tumor tissue following neoadjuvant therapy for NSCLC (12,13). The degree of pathologic response in patients with resectable NSCLC has been shown to correlate with survival outcomes, including overall survival (OS) and disease-free survival (DFS) (12,14-17). This information can influence subsequent treatment decisions, potentially allowing for treatment de-escalation in patients who respond to treatment or intensification in those with poor responses (14,18). However, the evaluation and interpretation of pathologic response in NSCLC present several challenges. For example, the heterogeneity of NSCLC tumors, variability in treatment responses, and limitations of current evaluation methods contribute to the complexity of pathologic response assessment (19). Moreover, neoadjuvant treatment with immunotherapy and targeted therapies results in pathologic response patterns that are distinct from those caused by chemotherapy, raising concerns about the usefulness of pathologic response as an indicator of treatment efficacy in different settings (20,21). Additionally, the emphasis on pathologic response as a primary indicator of treatment success in clinical trials has raised concerns about overlooking long-term outcomes, such as OS and quality of life (22). Although pathologic response is a valuable early indicator of treatment efficacy, it is crucial to recognize its limitations in both clinical trials and practice.

While the increasing use of neoadjuvant therapy in NSCLC has magnified the importance of pathologic response as an endpoint, it is premature to use postoperative pathological status as the sole determinant for guiding adjuvant treatment decisions, as such a strategy may fail to achieve optimal clinical benefits for patients. Significant optimization is still needed across the entire spectrum of pathologic response assessment, from the fundamental histopathologic evaluation to the clinical interpretation of its prognostic value for long-term survival. Therefore, in this article, we consider the evaluation of pathologic response in NSCLC across different treatment modalities and discuss the relationship between pathologic response and long-term outcomes, including the limitations and challenges in interpreting pathologic response as a surrogate endpoint for survival outcomes. By providing a balanced and critical evaluation of the current evidence on pathologic response in NSCLC, this review aims to support clinicians in optimizing treatment strategies to improve both short-term and long-term outcomes. We present this article in accordance with the Narrative Review reporting checklist (available at https://tlcr.amegroups.com/article/view/10.21037/tlcr-2025-584/rc).

Methods

We searched PubMed using the keywords “non-small cell lung cancer” OR “NSCLC” AND pathologic response” OR “pathological response” OR “pathology” OR “neoadjuvant” from database inception until June 2025 without language restrictions. The search strategy is summarized in Table S1. We manually filtered the search results to identify articles proposing guidelines or approaches to the pathologic assessment of NSCLC, articles describing challenges in assessing pathologic response in NSCLC, and studies reporting pathologic response to neoadjuvant treatment and/or the association between pathologic response and survival outcomes. Data were extracted and summarized descriptively.

Current methods of evaluating pathologic response

Methods used to evaluate pathologic response in NSCLC include gross examination, histopathologic assessment, immunohistochemistry, and molecular techniques (19). The initial step in evaluating pathologic response involves gross examination of the resected tissue to identify the tumor bed where the original pretreatment tumor was located (19). Computed tomography (CT) scans of the chest may also aid in the identification of the tumor bed, particularly in cases with complete tumor regression (19). Although gross examination provides valuable insights into the effects of treatment on tumor size and morphology, it has limited ability to distinguish between viable tumor cells and treatment-induced changes, necessitating more detailed histological analysis (19). Histopathologic assessment of resected tumor tissues involves the microscopic evaluation of the percentages of viable tumor, necrosis, and stroma (including inflammation and fibrosis) (19). The percentage of residual viable tumor cells is a key histopathologic measure of response, defined as the proportion of viable tumor cells remaining after treatment in relation to the total tumor bed (13,19). A major pathologic response (MPR) is defined as ≤10% viable tumor cells, and a pathologic complete response (pCR) as no viable tumor cells (12,13,19). Immunohistochemistry for specific immune cell markers (e.g., CD8⁺ T cells) and multiplex immunofluorescence are increasingly being employed to characterize the immune landscape of resected tumors from patients treated with immune checkpoint inhibitors (ICIs) (21,23).

Challenges in evaluating pathologic response in NSCLC

Variability in pathologic response assessment

NSCLC tumors exhibit high levels of molecular heterogeneity, not only between patients, but also within single tumors (24-26). Due to intratumor heterogeneity, tumors may exhibit varying degrees of response to treatment within different regions, which presents a considerable challenge in accurately assessing pathologic response (26). For example, the expression of programmed death receptor 1 (PD-1) and programmed death-ligand 1 (PD-L1) has been shown to vary considerably between regions of the same tumor in patients with NSCLC, resulting in intratumoral variations in anti-PD-1 resistance scores (27,28). Consequently, a single biopsy or tissue sample may not capture the full spectrum of tumor diversity, potentially leading to sampling bias and incomplete or misleading information about the tumor’s composition and behavior. Recent evidence suggests that traditional tumor grossing methods (at least one tumor section per the greatest tumor diameter) are insufficient in capturing residual viable tumor cells in patients with NSCLC who received neoadjuvant therapy (29). In a simulation analysis of resected NSCLC specimens pretreated with ICIs, either alone or in combination with chemotherapy, traditional tumor grossing methods accurately identified MPR and pCR in only 87% and 81% of cases, respectively, compared with submission of the entire tumor bed (29). This analysis indicated that accurate residual viable tumor scoring requires submission of the entire residual primary tumor or at least 20 tumor sections (29). Although adequate sampling of the entire tumor bed can help improve representative sampling and increase the accuracy of pathologic response evaluation, sampling the entire tumor bed can be impractical, particularly in large tumors or those with complex spatial distributions (30-32). Furthermore, identification of the tumor bed may be difficult in cases where the original tumor treatment response is MPR or pCR (19). This is particularly relevant for patients with squamous cell carcinoma, who tend to have better responses to neoadjuvant chemotherapy compared with those with adenocarcinoma (33). In our clinical experience, only localized scars within the bronchi may be observed after treatment (most commonly immunotherapy, as this is the most widely used neoadjuvant therapy) for central squamous cell carcinoma (34,35). Additionally, reactive changes in the surrounding lung tissue after treatment can be difficult to distinguish from the tumor bed (19). CT images before and after treatment, and sutures placed by the surgeon at the original tumor location, can help to confirm the tumor bed (19).

Neoadjuvant therapies can induce various histological changes that may be difficult to differentiate from residual viable tumor (32,36). Moreover, different therapeutic modalities can induce distinct patterns of tumor regression and tissue changes, complicating the evaluation of pathologic response (35,37). This challenge is pronounced in the context of immunotherapy, where dense lymphocytic infiltrates and granulomatous inflammation can obscure or mimic residual tumor cells (19). Time-dependent changes in pathological features can also present difficulties in accurately evaluating pathologic response in NSCLC (32). The timing of surgery following neoadjuvant therapy can significantly impact the observed pathological changes (38,39). Early surgery may underestimate the full extent of treatment response, whereas delayed surgery may allow for tumor regrowth in non-responders. The optimal timing for response assessment remains to be determined (38).

Limited standardization of current assessment methods

The accurate measurement and reporting of viable tumor cells after treatment is crucial for determining pathologic response and guiding subsequent treatment decisions (19). However, there is currently no standardized method for collecting data and quantifying residual tumor burden, leading to variability in assessment methods and reporting practices across institutions and studies (13). The International Association for the Study of Lung Cancer (IASLC) provided the first guidelines for the pathologic assessment of lung cancer resection specimens after neoadjuvant therapy, regardless of the type of neoadjuvant therapy given (19). Further development of the sampling and assessment methodology was subsequently proposed (13). Immune-related pathologic response criteria (irPRC) have also been published for pathological assessment of response to neoadjuvant therapy, specifically in patients who received PD-1 inhibitors (20). The IASLC criteria focus solely on the residual viable tumor of the primary tumor and evaluate histologic features of necrosis, stromal tissue, and viable tumor as a percentage of the total tumor bed, with the response rate calculated as the percent of viable tumor (13). In contrast, the irPRC includes evaluation of both the primary tumor and lymph node metastasis and includes assessment of a greater range of pathologic features of the regression bed (the area of immune-mediated tumor clearance), including immune activation (lymphoid infiltrates, tertiary lymphoid structures), massive tumor cell death (cholesterol clefts), and tissue repair (neovascularization, proliferative fibrosis) to calculate residual viable tumor (20). However, these recommendations are based on limited evidence, and controversies remain (32).

The lack of consensus on the optimal method for quantifying residual tumor burden can result in inconsistent reporting and difficulties in comparing results across studies. For example, in a study comparing different criteria for estimating MPR in patients with NSCLC after neoadjuvant immuno-chemotherapy, the MPR rate was higher with the IASLC criteria vs. the irPRC (63.4% vs. 57.4%, respectively) (40). No disease recurrence was observed during the study period in 6% of patients with inconsistent MPR status. In addition, although MPR statuses with both criteria were significantly associated with improved event-free survival (EFS), the IASLC criteria were superior to the irPRC in predicting EFS, with a higher area under the curve (AUC) value (0.65 vs. 0.62, respectively) (40).

Inter-observer variability in tumor assessment due to the subjective nature of histological scoring is another challenge in evaluating pathologic response in NSCLC (13,32). Factors contributing to this variability include differences in experience, training, and individual interpretation of morphological features (32). Nonetheless, available studies suggest acceptable levels of concordance (20,33). High inter-observer reproducibility was observed between experienced pathologists using increments of 5% to record viable tumor cells after neoadjuvant chemotherapy in 272 patients with stage II–III NSCLC (33). Similarly, when three observers with varying expertise assessed resection specimens from 108 patients with NSCLC who underwent surgery after neoadjuvant chemotherapy, there was robust reproducibility in tumor bed delineation, although this was reduced with smaller tumor beds in squamous cell carcinoma (41). In addition, a small study of resection specimens from 20 patients with NSCLC who received neoadjuvant nivolumab demonstrated a median 5% variability in histopathologic features (range, 0–29%) when four pathologists analyzed the samples (20).

Limited availability and standardization of biomarkers

Although several biomarkers have been identified for assessment of response to neoadjuvant therapy in resectable NSCLC, their clinical use remains to be defined (21). High pre-treatment PD-L1 expression and high tumor mutation burden (TMB) have been associated with MPR and pCR in a meta-analysis of data from patients receiving neoadjuvant immunotherapy for NSCLC (42). Nonetheless, wide variability in results of biomarker assessment with PD-L1 and TMB has been reported across different studies (21). Emerging evidence supports the use of circulating tumor DNA (ctDNA), a minimally invasive liquid biopsy method for tumor sampling, for identifying high-risk patients who may benefit from treatment escalation or switching during neoadjuvant immunotherapy or after tumor resection (43). However, data from prospective studies are required to support the wider implementation of ctDNA testing (43). Furthermore, a study investigating gene expression profiles in tumor samples from patients with resectable NSCLC treated with neoadjuvant immuno-chemotherapy suggested that interferon-responsive genes (IFNG, GZMB, and NKG7), as well as M1 macrophages, could potentially outperform PD-L1 and TMB as biomarkers of pCR following immunotherapy (44). The results also showed that high expression levels of genes related to proliferation and tumor markers after treatment were associated with poor pathologic response to neoadjuvant immuno-chemotherapy (44). Additionally, high baseline and preoperative neutrophil-to-lymphocyte ratios have been found to predict poor pathologic response in patients with NSCLC undergoing neoadjuvant chemotherapy with or without PD-1 inhibitors, and may have potential as a screening tool in this patient population (45). Tertiary lymphoid structures and spatial T-cell phenotypes are emerging potential biomarkers for pathologic response in NSCLC following neoadjuvant therapy. Tertiary lymphoid structures, organized immune cell clusters in non-lymphoid tissues, have been associated with achievement of MPR following neoadjuvant therapy (46). T-cell phenotypes within NSCLC tumors may also provide a biomarker of response to neoadjuvant treatment (47).

Metabolic parameters measured with ¹⁸F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/CT have also been investigated as biomarkers of response to neoadjuvant immunotherapy in NSCLC. The results from multiple studies suggest that ¹⁸F-FDG PET/CT parameters, both pre-treatment and changes following treatment, may be able to predict pathologic response (48-52). In particular, maximum standardized uptake value (SUV_max), a measure of glucose metabolism, appears to have promise as a biomarker of pathologic response. However, further large-scale studies are required to validate these biomarkers for clinical use.

Challenges in interpreting pathologic response in NSCLC patient management and treatment decision-making

Pathologic responses to neoadjuvant therapies in NSCLC

Chemotherapy

Neoadjuvant chemotherapy is widely used for the treatment of operable NSCLC (38). However, as a single modality, neoadjuvant chemotherapy provides limited pathologic response benefit in patients with NSCLC (Table 1).

Table 1. Key phase 2/3 studies reporting pathologic responses to neoadjuvant therapies in NSCLC.

Author, year	Study	Phase	Number of patients	Treatment	MPR [95% CI], %	pCR [95% CI], %	Median EFS/PFS/RFS/DFS [95% CI], months	Median OS [95% CI], months
Chemotherapy
Forde et al., 2022 (53)	CheckMate 816	3	179	Platinum-doublet chemotherapy	8.9 [3.6–10.26]	2.2 [0.6–5.6]	EFS: 20.8 [14.0–26.7]	NR [NR–NR]
Wakelee et al., 2023 and Spicer et al., 2024 (54,55)	KEYNOTE-671	3	400	Cisplatin-based chemotherapy	11.0 [8.1–14.5]	4.0 [2.3–6.4]	EFS: 18.3 [14.8–22.1]	52.4 [45.7–NR]
Lu et al., 2024 (56)	Neotorch	3	202	Platinum-based chemotherapy	8.4 [5.0–13.1]	1.0 [0.1–3.5]	EFS: 15.1 [10.6–21.9]	30.4 [29.2–NR]
Provencio et al., 2023 (57)	NADIM	2	29	Paclitaxel + carboplatin	14 [4–32]	7 [1–23]	PFS: 15.4 [10.6–NR]	NR [21.1–NR]
Chemoradiotherapy
Rusch et al., 2007 (58)	Intergroup Trial 0160	2	110	Radiation + cisplatin + etoposide	NP	56	NP	33
Immunotherapy
Cascone et al., 2023 (59)	NEOSTAR	2	21	Nivolumab + ipilimumab	50 [25–75]	38 [15–65]	RFS: NR	NR
Cascone et al., 2023 (59)	NEOSTAR	2	23	Nivolumab	24 [8–47]	10 [1–30]	RFS: NR	NR
Wislez et al., 2022 (60)	IFCT-1601 IONESCO	2	46	Durvalumab	19	7	DFS: NR	NR
Immuno-chemotherapy
Forde et al., 2022 (53)	CheckMate 816	3	179	Nivolumab + platinum-doublet chemotherapy	36.9 [29.8–44.4]	24.0 [18.0–31.0]	EFS: 31.6 [30.2–NR]	NR [NR–NR]
Wakelee et al., 2023 and Spicer et al., 2024 (54,55)	KEYNOTE-671	3	397	Pembrolizumab + cisplatin-based chemotherapy	30.2 [25.7–35.0]	18.1 [14.5–22.3]	EFS: 47.2 [32·9 to NR]	NR [NR–NR]
Lu et al., 2024 (56)	Neotorch	3	202	Toripalimab + platinum-based chemotherapy	48.5 [41.4–55.6]	24.8 [19.0–31.3]	EFS: NR [24.4–NR]	NR [NR–NR]
Provencio et al., 2023 (57)	NADIM	2	57	Nivolumab + chemotherapy	53 [39–66]	37 [24–51]	PFS: NR [27.6–NR]	NR [33.5–NR]
Cascone et al., 2023 (61)	NEOSTAR	2	22	Nivolumab + chemotherapy	32.1 [18.7–43.1]	18.2 [5.2–40.3]	EFS: NR	NR
Cascone et al., 2023 (61)	NEOSTAR	2	22	Nivolumab + ipilimumab + chemotherapy	50.0 [34.6–61.1]	18.2 [5.2–40.3]	EFS: NR	NR
Cascone et al., 2024 (62)	CheckMate 77T	3	229	Nivolumab + chemotherapy	35.4 [29.2–41.9]	25.3 [19.8–31.5]	EFS: NR [28.9–NR]	NP
Yue et al., 2025 (63)	RATIONALE-315	3	226	Tislelizumab + chemotherapy	56 [50–63]	41 [34–47]	NR	NR
Heymach et al., 2023 (64)	AEGEAN	3	400	Durvalumab + chemotherapy	33.3 [28.5–38.4]	17.2 [13.5–21.5]	EFS: NR [31.9–NR]	NP
Chemoradiotherapy + immunotherapy
Bahce et al., 2024 (65)	INCREASE study	2	30	Chemoradiotherapy + ipilimumab and nivolumab	73 [52–88]	58 [37–77]	NP	NP
TKIs
Zhong et al., 2023 (66)	EMERGING-CTONG 1103	2	72	Erlotinib	9.7	0	PFS: 21.5 [16.6–26.4]	42.2 [29.8–54.6]
Bian et al., 2023 (67)	Bian et al.	2	47	Afatinib	9.1 [1.9–24.3]	3.0	EFS: NR	NP
Chang et al., 2024 (68)	ASCENT	2	19	Afatinib + chemoradiotherapy	40	10	PFS: 2.63 years [1.41–3.07]	5.76 years [2.45–NR]
Lv et al., 2023 (69)	NEOS	2b	40	Osimertinib	10.7 [3.7–27.2]	3.6 [NP]	NP	NP
Blakely et al., 2024 (70)	Blakely et al.	2	27	Osimertinib	14.8 [4.2–33.7]	0	DFS: 40.9 [26.0–NR]	NR
Zhang et al., 2021 (71)	Zhang et al.	2	33	Gefitinib	24.2 [11.9–40.4]	NP	DFS: 33.5 [19.7–47.3]	NR
He et al., 2025 (72)	NeoADAURA	3	121	Osimertinib + chemotherapy	26 [18–34]	4 [1–9]	NR	NP
He et al., 2025 (72)	NeoADAURA	3	117	Osimertinib	25 [17–34]	9 [4–15]	NR [30.3–NR]	NP
Anti-angiogenic therapies
Chaft et al., 2013 (73)	Chaft et al.	2	41	Bevacizumab + cisplatin + docetaxel	27 [14–43]	NP	RFS: 54 [24–NR]	NR
Tsutani et al., 2024 (74)	NAVAL	2	30	Bevacizumab + cisplatin + pemetrexed	NP	12.0	NP	NP
Zhao et al., 2023 (75)	Zhao et al.	2	78 (treated); 65 (R0 resected)	Camrelizumab + apatinib	Treated: 47 [36–59]; R0 resected: 57 [44–69]	Treated: 19 [11–30]; R0 resected: 23 [14–35]	NP	NP
Duan et al., 2024 (76)	TD-NeoFOUR	2	45	Neoadjuvant sintilimab + anlotinib + chemotherapy, then adjuvant sintilimab	ITT: 66.7 [52.1–78.6]; PPS: 73.2 [58.1–84.3]	ITT: 57.8 [43.3–71.0]; PPS: 63.4 [48.1–76.4]	ITT, EFS: NR [25.1–NR]	ITT: NR [NR–NR]

CI, confidence interval; DFS, disease-free survival; EFS, event-free survival; ITT, intention-to-treat; MPR, major pathologic response; NP, not provided; NR, not reached; NSCLC, non-small cell lung cancer; OS, overall survival; pCR, pathologic complete response; PFS, progression-free survival; PPS, per-protocol set; RFS, recurrence-free survival; TKI, tyrosine kinase inhibitor.

The limited MPR with neoadjuvant chemotherapy alone has also been confirmed in two real-world studies (77,78).

Pathologic response patterns after neoadjuvant chemotherapy include necrosis, fibrosis, foam cell infiltration, cholesterol clefts, and inflammation (36). However, these histological changes may also be present in the resected tumors of patients who did not receive neoadjuvant chemotherapy, which can complicate assessment of pathologic response (36).

Radiotherapy

The limited data available suggest that neoadjuvant radiotherapy alone does not improve resectability or survival in patients with NSCLC (18). However, neoadjuvant radiotherapy can achieve high rates of pathologic response when combined with chemotherapy (58,79).

Although focused on stage III unresectable NSCLC, the PACIFIC trial demonstrated the potential of concurrent chemoradiotherapy followed by immunotherapy, setting the stage for similar approaches in the neoadjuvant setting for resectable disease (80). In the single-arm, phase 2 INCREASE trial involving patients with resectable and borderline resectable NSCLC, neoadjuvant chemoradiotherapy combined with ipilimumab and nivolumab was associated with an MPR rate of 73% and a pCR rate of 58% among the 26 patients who underwent resection (Table 1) (65). However, despite the promising efficacy of neoadjuvant chemoradiotherapy in patients with resectable NSCLC, it is important to balance the treatment benefits with the potential for toxicity and the complexity of the regimen (79).

Evaluating pathologic responses after neoadjuvant radiotherapy alone or in combination with other treatments can be challenging. Neoadjuvant radiotherapy induces distinct histopathologic changes, including radiation-induced fibrosis and vascular changes (81). Distinguishing viable tumor cells from radiation effects can be difficult and is further complicated by the time-dependent nature of radiation-induced changes (82).

Immunotherapy

A systematic review and meta-analysis of 18 studies involving 548 patients with resectable NSCLC demonstrated an MPR rate of 52% and a pCR rate of 24% after neoadjuvant immunotherapy (83). The addition of a second ICI can improve pathologic responses compared with single-agent immunotherapy (59). In the first part of the phase 2 NEOSTAR trial, which evaluated neoadjuvant nivolumab with or without ipilimumab in patients with operable NSCLC, the MPR rate in patients who underwent resection on study was 38% with nivolumab plus ipilimumab compared with 22% with nivolumab alone (Table 1) (59). Nivolumab plus ipilimumab also resulted in higher pCR rates (38% vs. 10%) and less viable tumor cells (median 9% vs. 50%) (59). Furthermore, dual therapy enhanced tumor immune infiltrates and immunologic memory, showing greater frequencies of effector and memory T cells (59).

Clinical data from phase 2 and 3 studies suggest that combining neoadjuvant immunotherapy with chemotherapy may provide better pathologic responses than neoadjuvant chemotherapy or immunotherapy alone in resectable NSCLC (Table 1) (53,54,56,57,61-64). Across these studies, MPR rates for neoadjuvant immunotherapy plus chemotherapy ranged from 30.2% to 56.2%, while pCR rates ranged from 18.1% to 40.7% (Table 1). In the second part of the NEOSTAR trial, which compared neoadjuvant chemotherapy plus nivolumab with or without ipilimumab, the addition of chemotherapy to dual immunotherapy further increased MPR (50.0%) and pCR (18.2%) rates (61). The addition of chemotherapy to dual immunotherapy also further enhanced immune responses (61).

Data from meta-analyses and retrospective studies support the benefit of combining ICIs and chemotherapy in the neoadjuvant setting for the treatment of patients with early-stage NSCLC (11,16,35). A meta-analysis including eight trials with a total of 3,387 patients reported that the pCR rate was significantly higher with neoadjuvant ICI plus chemotherapy (from 17.2% to 40.7%) compared with chemotherapy alone (from 1.0% to 8.9%) (11). In a second meta-analysis, data from eight trials showed that neoadjuvant immuno-chemotherapy was associated with a higher MPR compared with neoadjuvant chemotherapy [odds ratio (OR) =6.19; 95% confidence interval (CI): 4.39–8.74; P<0.00001] (16). In addition, patients with PD-L1 expression ≥1% were more likely to achieve an MPR (OR =2.21; 95% CI: 1.28–3.82; P=0.004) (16). A further meta-analysis of 16 studies involving 988 patients demonstrated that neoadjuvant immuno-chemotherapy provided higher pathologic response rates than single-agent immunotherapy (MPR: 53.3% vs. 28.6%; pCR: 28.6% vs. 9.9%), with no significant increase in adverse events or surgical delay rates (84). Retrospective real-world data confirm clinical findings demonstrating improved pathologic responses with neoadjuvant immuno-chemotherapy compared with neoadjuvant chemotherapy alone (35,85-87).

The two main subtypes of NSCLC, squamous cell carcinoma and adenocarcinoma, have distinct immunologic features and therefore may respond differently to neoadjuvant immunotherapy (88). A meta-analysis of six trials of perioperative immuno-chemotherapy, including 3,003 patients, showed that those with squamous compared with non-squamous NSCLC had greater MPR (OR =0.61; 95% CI: 0.45–0.82) and pCR (OR =0.68; 95% CI: 0.49–0.95) benefits (89). Conversely, a meta-analysis of 22 trials of neoadjuvant immunotherapy, including 430 patients, found no significant differences in pathologic response between patients with squamous cell carcinoma and adenocarcinoma, either for ICI monotherapy or immuno-chemotherapy (90). Further studies are required to determine the optimal treatment based on tumor histology.

Treatment with ICIs promotes several histopathologic changes that can complicate the interpretation of residual tumor burden (19,20). In treatment-responsive tumors, the tumor is replaced by fibroinflammatory areas (regression beds) that do not necessarily lead to a reduction in the volume of the tumor bed (19,20). Characteristics of regression beds include features of immune activation, including high numbers of tumor-infiltrating lymphocytes, tertiary lymphoid structures, and plasma cells, as well as cholesterol clefts, tissue fibrosis, and neovascularization (20). These immune-related changes can persist even after complete tumor eradication, necessitating careful interpretation to avoid overestimation of residual disease (20).

Tyrosine kinase inhibitors (TKIs)

The efficacy of neoadjuvant treatment with TKIs in patients with NSCLC harboring epidermal growth factor receptor (EGFR) mutations or anaplastic lymphoma kinase (ALK) fusions has been studied in clinical trials (91,92), although data on the effects of treatment on pathologic response remain limited (66-71). With single-agent EGFR-targeted TKIs, reported MPR rates range from 9.1% to 40.0%, and pCR rates from 0.0% to 10.0% (Table 1). Therapies targeted against ROS1, MET, and RET have been investigated in small-scale studies or case reports and require further investigation (92,93).

The modest pathologic responses may reflect the mechanism of action of TKIs, which mainly results in inhibition of the proliferation of tumor cells rather than their eradication, as well as possible tumor flare responses to treatment (94-96). Future trials are likely to focus on combination strategies. For example, in the phase 2 ASCENT study, the combination of neoadjuvant afatinib with chemoradiation therapy provided a 40% MPR rate and a 10% pCR rate in ten patients who underwent surgery (68). In the NeoADAURA phase 3 trial, neoadjuvant osimertinib plus chemotherapy resulted in an MPR rate of 26% vs. 25% with osimertinib monotherapy and 2% with chemotherapy alone (72). Pathologic response may be limited as an endpoint in neoadjuvant trials involving TKIs, and the correlation of pathologic response to neoadjuvant TKIs with survival outcomes has not been validated (12,94). The optimal endpoints in the neoadjuvant TKI setting remain uncertain, although it is possible that objective response rates, which range from approximately 50% to 70% in reported trials (66,67,69,71), may have greater clinical value than pathologic response.

Acquired T790M mutations, MET amplification, and PIK3CA mutations have been identified as mechanisms of resistance to EGFR-targeted TKIs in EGFR-mutant lung tumors (97). These alterations should be taken into account when considering the use of neoadjuvant TKIs in patients with NSCLC. Data on histopathologic features following neoadjuvant TKI therapy are scarce (19).

Anti-angiogenic therapies

Data on pathologic response rates with neoadjuvant anti-angiogenic therapy in patients with NSCLC remain limited. A phase 2 study of neoadjuvant bevacizumab plus chemotherapy in patients with resectable nonsquamous NSCLC showed a 27% MPR rate (73), and in another trial of the combination, 12% of patients had a pCR (74). The use of bevacizumab plus chemotherapy in the neoadjuvant setting is associated with potential safety concerns, including the risk of perioperative complications such as gastrointestinal bleeding and bronchopleural fistulization (73). Combined anti-angiogenic and immunotherapy strategies have since been investigated in this setting. Treatment with neoadjuvant apatinib, a small-molecule angiogenesis inhibitor, has demonstrated antitumor activity in combination with the anti-PD-1 antibody camrelizumab; an MPR was achieved by 57% of R0-resected patients, and pCR by 23% (75). Neoadjuvant anlotinib, an anti-angiogenic receptor TKI targeting vascular endothelial growth factor receptor (VEGFR)-1, VEGFR-2, VEGFR-3, c-Kit, and platelet-derived growth factor receptor (PDGFR)-β, has also recently demonstrated notable antitumour effects when used in combination with perioperative anti-PD-1 antibody sintilimab, with 66.7% of patients with resectable NSCLC achieving an MPR, and 57.8% achieving a pCR (76). Owing to the positive antitumorigenic effects of combined anti-PD-1 and anti-angiogenic therapeutic strategies in this setting, studies have since investigated the efficacy of anti-PD-1/vascular endothelial growth factor (VEGF) bispecific antibodies for neoadjuvant treatment of NSCLC (98).

General challenges

In addition to the therapy-specific challenges described, there are more general challenges associated with interpreting pathologic responses in NSCLC. For example, assessing a pathologic response in the presence of lymphovascular invasion. We recommend that a pCR in the presence of lymphovascular invasion is described as ‘no residual invasive carcinoma identified in the tumor bed, however, the foci of lymphovascular invasion, containing viable tumor cells, are present’. We advise that the presence of lymphovascular invasion must be explicitly stated in the pathology report. Histologic mimics are another potential confounding factor when evaluating NSCLC sections for pathologic response. Features such as organizing pneumonia (99), foamy histiocytes (100), and granulomatous inflammation (101) can be mistaken for residual tumor or may obscure small tumor nests. There is also some evidence that systemic therapy can induce organizing pneumonia (102-104). This emphasizes the vital role of experienced pathologists. Other questions remain to be answered, such as how to define the boundaries of the tumor bed and whether ypN0(i+) should be considered a pCR.

The potential for discordance between radiographically evaluated response and pathologic response has been reported (105) and represents a challenge for evaluating treatment response. For immunotherapy, radiologic imaging may show stable or even enlarged lesions due to inflammation “pseudoprogression”, while pathology reveals a pCR (106). Conversely, with TKI therapy, significant tumor shrinkage on imaging may correspond to a poor pathologic response (107).

Association between pathologic response and survival outcomes

A strong association between pathologic response and improved EFS has been demonstrated in patients with resectable NSCLC (14-17,108,109). The association between pathologic response and OS is less clear (14-17,108,109). Although some meta-analyses have reported a statistically significant association between pCR and OS, the strength of the association (for example, the R²) is often only moderate. This suggests that long-term survival outcomes cannot be predicted by pCR alone. Furthermore, the pCR-survival relationship is mostly evaluated at the patient level, with patients who achieve a pCR tending to have a better prognosis than those who do not. However, using pCR as a basis for drug approvals or changes in clinical practice requires demonstration of consistent effects at the trial level. It should be noted that pCR exhibits high variability across studies, for example, the pCR rate reported in RATIONALE-315 was almost double that reported in KEYNOTE-671 (40.7% vs. 22.3%) (54,63), yet the differences in EFS and OS across studies are relatively small (Table 1). Therefore, predicting long-term outcomes using pCR alone remains premature and should be conducted with caution.

In a meta-analysis of patient-level data from studies of neoadjuvant therapy with or without radiotherapy, pCR and MPR were associated with EFS and OS (15). Patients with vs. without a pCR had better EFS [hazard ratio (HR) =0.49; 95% CI: 0.41–0.60] and OS (HR =0.49; 95% CI: 0.42–0.57). Similarly, patients with vs. without an MPR had better EFS (HR =0.52; 95% CI: 0.42–0.66) and OS (HR =0.36; 95% CI: 0.29–0.44) (15). In a meta-analysis using patient-level data from 24 studies in 6,274 patients treated with neoadjuvant chemotherapy with or without radiotherapy, pCR was also associated with EFS (HR =0.46; 95% CI: 0.37–0.57) and OS (HR =0.50; 95% CI: 0.45–0.56) (14). Real-world data from 425 patients receiving neoadjuvant chemotherapy or chemoradiotherapy further support the value of pCR as an early indicator of improved EFS (adjusted HR =0.44; 95% CI: 0.28–0.68) and OS (adjusted HR =0.50; 95% CI: 0.29–0.85) (108).

Meta-analyses have also been conducted to investigate the association between pathologic response and EFS and OS in patients who received neoadjuvant immunotherapy (16,109). A meta-analysis of 53 trials in patients who received neoadjuvant immuno-chemotherapy or chemotherapy alone found that MPR was predictive of DFS/progression-free survival (PFS)/EFS (HR =0.28; 95% CI: 0.10–0.79; P=0.02) and OS (HR =0.80; 95% CI: 0.72–0.88; P<0.0001) (16). However, the association of MPR with survival outcomes was not assessed by neoadjuvant treatment type. Findings from a meta-analysis of seven randomized clinical trials involving 2385 patients who were treated with neoadjuvant ICIs alone or in combination with chemotherapy showed a strong correlation between pCR and MPR with 2-year EFS (R² of 0.82 and 0.81, respectively) at the patient level (109). However, the correlation of pCR and MPR with OS was not robust (R² of 0.55 and 0.52, respectively) (109). In the CheckMate 816 trial, which evaluated neoadjuvant immunotherapy plus chemotherapy vs. chemotherapy alone, pathologic response was a better predictor of EFS compared with radiographic response and ctDNA clearance (17). The relationship between pathologic response and EFS held true regardless of lymph node involvement (17).

Despite the reported associations between pathologic response and survival outcomes at the patient level, the existing evidence does not fully support pathologic response as a surrogate endpoint of survival outcomes at the trial level (15,110). However, it should be noted that the proportion of patients achieving a pCR is small and therefore the statistical representation of this subgroup is limited, which may weaken the observed correlation between pCR and OS at the trial level. Further research is needed to establish a surrogate endpoint applicable at both the patient and trial levels. In the meantime, pathologic response should not be considered as the sole primary endpoint in the design of clinical trials, and more attention should be given to long-term outcomes such as EFS and OS. Moreover, various thresholds of residual viable tumor cells are being explored beyond pCR and MPR to refine prognostic assessments (17). The rarity of pCR in NSCLC, which is typically <10% with chemotherapy alone (53,54,56,57), has historically limited its utility as a primary endpoint. However, the advent of immunotherapy and targeted therapies has increased pCR rates (9-11), renewing interest in this endpoint. Variability in the definition and assessment of pathologic response across different studies can complicate the interpretation of results and hinder the ability to compare outcomes across trials (14). It should also be noted that some patients who achieve pCR may still experience disease recurrence or progression, whereas others with residual disease may have prolonged survival (36). Intermediate levels of response may still confer survival benefits, and the binary nature of these endpoints may oversimplify the complex mechanisms underlying treatment responses. Therefore, integration of pathologic response with other prognostic factors is needed (36).

Optimal treatment strategy for patients achieving a pathologic response

The decision to use adjuvant therapy following achievement of a pathologic response with neoadjuvant therapy is complex and presents a paradox. On one hand, achieving a pCR or MPR is itself associated with favorable long-term survival outcomes such as EFS and OS (14-16,108,109), suggesting adjuvant therapy is not required. On the other hand, if a patient has a strong response to neoadjuvant therapy, then it suggests they may also benefit from further systemic treatment. When considering adjuvant therapy following a pCR or MPR, it should be recognized that a pathologic response alone may not fully capture tumor biology and the potential for residual disease or treatment resistance. Therefore, achieving a pCR or MPR should not be viewed as the ultimate treatment goal. Another important consideration is that the pCR result may not be reliable for all patients, with evidence from phase 3 studies suggesting that some patients with an apparent pCR will develop disease recurrence within the first 12 months of resection (54,62). In cases where an MPR is achieved, adjuvant therapy may still be warranted to address any residual disease and minimize the risk of recurrence.

Data on the benefits of adjuvant immunotherapy are inconclusive. Two meta-analyses have indicated that adding adjuvant immunotherapy to neoadjuvant immunotherapy plus chemotherapy does not significantly improve EFS or OS and increases the incidence of treatment-related adverse events (111,112). However, a retrospective study has suggested that patients who achieve an MPR may benefit from adjuvant immunotherapy (113). The choice of adjuvant therapy depends on several factors. For patients who received neoadjuvant chemotherapy, continuing with the same or a similar regimen in the adjuvant setting is common practice. In the case of neoadjuvant immunotherapy, the NADIM trial showed promising results in patients who continued nivolumab for 1 year after surgery (114,115). However, the optimal duration of adjuvant immunotherapy remains to be determined. For patients with EGFR mutations who received neoadjuvant TKIs, continuing the same targeted therapy in the adjuvant setting is generally recommended, based on extrapolation from adjuvant trials such as ADAURA (116). Continuous monitoring of patients after surgery is crucial, especially for those who achieved MPR rather than pCR. Studies have indicated that patients with an MPR may still have a risk of recurrence, necessitating vigilant follow-up and potential adjuvant therapy (117,118). Regular imaging and biomarker assessments can help detect recurrence early and allow for timely intervention. The use of ctDNA as a biomarker to assess minimal residual disease status can guide decisions regarding the necessity and intensity of adjuvant therapy (119-121).

Focusing solely on pathologic response when developing treatment plans may lead to the neglect of other important factors that influence patient outcomes, such as surgical complications, quality of life, and treatment-related toxicities. Pathologic response should be considered alongside other prognostic factors, including clinical stage, molecular profile, and patient characteristics, to achieve more comprehensive risk stratification and develop personalized treatment strategies (122). In terms of post-recurrence treatment strategies, this is a complex topic, with treatment selection guided by prior therapy use and molecular testing, and is beyond the scope of this review.

Future directions

In the future, next-generation sequencing technologies, which to date have largely been used in the advanced-stage NSCLC setting, will play an increasing role in understanding tumor biology and identifying patients who are likely to benefit from neoadjuvant and adjuvant therapies in early-stage NSCLC (123). Digital spatial profiling, which enables multiplex spatial analysis of proteins and RNA in tissue sections, also has potential for providing insights into the tumor microenvironment and treatment-induced changes (124).

Recent advances in artificial intelligence (AI) have shown promise in enhancing the accuracy and reproducibility of pathologic response evaluation in NSCLC. For example, Dacic et al. (125) used both visual techniques and a convolutional neural network (CNN) model to measure the percentage of viable tumor in resected specimens from patients with early-stage NSCLC who underwent neoadjuvant treatment with atezolizumab. The CNN model predicted visually assessed MPR with an AUC of 0.98, and digitally assessed MPR was associated with longer DFS and OS compared with no MPR. In addition, She et al. (126) developed a deep learning model using CT images to predict MPR in patients with NSCLC undergoing surgery after neoadjuvant immuno-chemotherapy. The model achieved an AUC of 0.73 in internal validation and 0.72 in external validation. Integrating clinical characteristics improved the model’s performance (126). Moreover, Nibid et al. tested five pre-trained CNNs to predict target volume reduction during chemoradiation treatment of stage III NSCLC, finding that CNNs were highly specific (true negative rate of 90.1) and sensitive (true positive rate of 0.75) (127). Building on these and previous findings, Rakaee et al. developed a deep learning-based ICI response prediction model using 295,581 image tiles from 958 patients that could predict PFS and OS in multivariate analysis; combining this model with PD-L1 scores achieved an AUC of 0.70 (95% CI: 0.63–0.76), outperforming either marker alone as a predictor of ICI response (128).

These findings support the use of AI-powered digital approaches in pathologic response assessments (125,126). However, several limitations hinder the integration of AI into clinical practice for evaluating pathologic responses in NSCLC. One significant challenge is the reliance on large, high-quality datasets for training machine learning models (129). Many existing datasets may be biased or unrepresentative of the broader patient population, which can lead to models that perform well in controlled environments but fail in real-world clinical settings (129). Moreover, although machine learning algorithms can achieve high accuracy, the lack of transparency in how decisions are made can lead to skepticism among clinicians (130). There is also the matter of explainability: i.e., without clinicians involved in training, models may be developed that include features that inherently increase model performance metrics, without regard to the underlying medical context, reducing trust in AI-based approaches. In view of this, Alice Natalina Caragliano et al. developed a model that integrates multiple CT views during training, allowing for high predictive performance with intrinsic explainability (131). Future directions may include the integration of explainable models to enhance transparency, interpretability, and clinical validation of AI tools used for predicting pathologic response in NSCLC.

Although pathologists play a crucial role in interpreting the biological significance of treatment effects, their involvement in the design and execution of clinical trials is often limited (132). This can lead to the implementation of assessment methods that do not align with the realities of pathological evaluation, resulting in potential biases and inaccuracies in trial outcomes (132). The integration of pathologists into clinical trial teams can facilitate the development of more relevant and practical assessment criteria that reflect the complexities of NSCLC biology and treatment responses (132,133). For instance, pathologists can contribute to the design of studies that incorporate novel biomarkers or imaging techniques to enhance response evaluation. Changes in the design of clinical trials are therefore required to ensure that pathologists are included as integral members of the research team, so they can play a critical role in clinical trial design, tissue sampling, and standardization of response assessment.

Conclusions

The evaluation of pathologic response in NSCLC presents several challenges, including the subjective nature of histopathologic evaluations, different patterns of histologic changes with different types of neoadjuvant therapy, and the lack of consensus on standardized protocols. Moreover, there is ongoing debate around the use of pCR as an endpoint in clinical trials due to uncertainty regarding its association with OS, as well as the use of pathologic response to guide treatment decisions after surgery.

In practical terms, we believe that submitting the entire tumor bed for large tumors is often impractical due to cost and time; 100% execution is difficult in real-world practice, especially when pathology departments are under immense pressure. Identifying the tumor bed in a field of dense fibrosis and inflammation requires experience. A less experienced pathologist or pathology assistant might be unable to accurately delineate the correct area to sample, leading to non-compliance with the spirit, if not the letter, of the guidelines. Pathology is a sampling science; if a small, 1 mm focus of residual viable tumor exists but is not included in the submitted sections, the case will be misclassified as a pCR. Similarly, the MPR calculation (≤10% viable tumor) is an estimate based on the sampled tissue. If the submitted slices are not truly representative of the entire tumor bed, the percentage can be skewed, leading to an incorrect assessment of MPR. Importantly, a pCR is a very impactful prognostic indicator for early-stage NSCLC. A patient who truly achieves a pCR may have an excellent prognosis, and misclassifying a patient as having a pCR provides false reassurance. An inaccurate assessment could lead directly to undertreatment.

Based on current evidence, the additional complexity of the irPRC may not offer a clear prognostic advantage over the simpler IASLC criteria in a routine clinical setting. This does not mean discarding the evaluation of lymph nodes but rather uncoupling this from the MPR definition. We believe pathologists should prioritize the IASLC criteria for the final MPR decision, as it appears to be a more robust predictor of patient survival, and report the detailed lymph node findings separately (40).

In summary, pathologic response is a valuable indicator of early response to treatment, but its current limitations necessitate a cautious and balanced approach in treatment decision-making for patients with early-stage resectable NSCLC, with consideration also given to other factors such as long-term survival and quality of life.

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