Clinical Oncology 종합 리뷰

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Neoadjuvant / Perioperative Immunotherapy연결 근거: neoadjuvant, perioperative, resectable, surgical attrition, pathologic response
  1. Methods방법론 색인 — 어떤 분석을 어떤 논문이 썼나연결어: neoadjuvant, perioperative, resectable
  2. Statistics통계 방법론 리뷰연결어: neoadjuvant, perioperative, resectable
  3. Yang 2024Treatment patterns and clinical outcomes of patients with resectable non-small cell lung cancer…연결어: neoadjuvant, perioperative, resectable
  4. Bang 2025Perioperative Pembrolizumab for Locally Advanced Thymic Epithelial Tumors: A Single-Arm, Phase…연결어: neoadjuvant, perioperative, pathologic response
  5. Forde 2025Overall Survival with Neoadjuvant Nivolumab plus Chemotherapy in Lung Cancer연결어: neoadjuvant, perioperative, resectable
  6. +44 more
Immunotherapy Response and Resistance연결 근거: pseudoprogression, dissociated response, acquired resistance, progressive disease, radiologic progression
  1. Methods방법론 색인 — 어떤 분석을 어떤 논문이 썼나연결어: pseudoprogression, acquired resistance, progressive disease
  2. Masse 2024[18F]FDG-PET/CT atypical response patterns to immunotherapy in non-small cell lung cancer patie…연결어: pseudoprogression, dissociated response, immune checkpoint inhibitors
  3. Wang 2022Spatial interplay patterns of cancer nuclei and tumor-infiltrating lymphocytes (TILs) predict c…연결어: progressive disease, immune checkpoint inhibitors, pembrolizumab
  4. ReviewBiomedical Imaging 종합 리뷰연결어: progressive disease, immune checkpoint inhibitors, pembrolizumab
  5. Statistics통계 방법론 리뷰연결어: progressive disease, immune checkpoint inhibitors, pembrolizumab
  6. +36 more
Extranodal Extension Imaging연결 근거: extranodal extension, ene, nodal
  1. Henson 2024Criteria for the diagnosis of extranodal extension detected on radiological imaging in head and…연결어: extranodal extension, ene, nodal
  2. Jang 2023Radiologic Extranodal Extension of Metastatic Lymph Nodes in Patients With Non-Small Cell Lung…연결어: extranodal extension, ene, nodal
  3. Jang 2023Radiologic Extranodal Extension of Metastatic Lymph Nodes in Patients With Non-Small Cell Lung…연결어: extranodal extension, ene, nodal
  4. Chohan 2025Pathological extranodal extension in head and neck cancer: A prognostic biomarker with therapeu…연결어: extranodal extension, ene, nodal
  5. ReviewBiomedical Imaging 종합 리뷰연결어: extranodal extension, ene, nodal
  6. +8 more
Radiomics and Radiogenomics연결 근거: radiomic, intratumor heterogeneity
  1. Methods방법론 색인 — 어떤 분석을 어떤 논문이 썼나연결어: radiomics, radiomic, radiogenomic
  2. ReviewBiomedical Imaging 종합 리뷰연결어: radiomics, radiomic, radiogenomic
  3. Statistics통계 방법론 리뷰연결어: radiomics, radiomic, radiogenomic
  4. Su 2023Radiogenomic-based multiomic analysis reveals imaging intratumor heterogeneity phenotypes and t…연결어: radiomics, radiomic, radiogenomic
  5. Henry 2022Investigation of radiomics based intra-patient inter-tumor heterogeneity and the impact of tumo…연결어: radiomics, radiomic, subsampling
  6. +21 more
Thoracic CT / PET Imaging연결 근거: ct, pet, pulmonary
  1. Methods방법론 색인 — 어떤 분석을 어떤 논문이 썼나연결어: ct, pet, pulmonary
  2. ReviewClinical Pulmonology 종합 리뷰연결어: ct, pet, pulmonary
  3. Statistics통계 방법론 리뷰연결어: ct, pet, pulmonary
  4. DeFreitas 2021Complications of Lung Transplantation: Update on Imaging Manifestations and Management연결어: ct, pet, pulmonary
  5. Cottin 2016Respiratory manifestations of eosinophilic granulomatosis with polyangiitis (Churg-Strauss)연결어: ct, pulmonary, egpa
  6. +64 more
Shared Tags이 논문의 tags: atezolizumab, durvalumab, neoadjuvant, nivolumab, pembrolizumab
  1. Xiong 2025Delta-radiomics features combined with haematological index predict pathological complete respo…공유 tag: atezolizumab, durvalumab, neoadjuvant, nivolumab
  2. Hirsch 2017PD-L1 Immunohistochemistry Assays for Lung Cancer Results from Phase 1 of the Blueprint PD-L1 I…공유 tag: atezolizumab, durvalumab, nivolumab, pembrolizumab
  3. Janjigian 2021Eradicating micrometastases with immune checkpoint blockade: Strike while the iron is hot공유 tag: atezolizumab, neoadjuvant, nivolumab, pembrolizumab
  4. Remon 2021Early and locally advanced non-small-cell lung cancer an update of the ESMO Clinical Practice G…공유 tag: atezolizumab, durvalumab, neoadjuvant, nivolumab
  5. Wang 2023Advances in efficacy prediction and monitoring of neoadjuvant immunotherapy for non-small cell…공유 tag: atezolizumab, neoadjuvant, nivolumab, pembrolizumab
  6. +67 more

개요

본 리뷰는 Clinical Oncology 카테고리 내 92편의 논문을 바탕으로 NSCLC 및 기타 고형암의 최신 치료 전략, 예후 인자, 그리고 방법론적 경향을 종합적으로 분석한다. 주요 초점은 EGFR/ALK wild-type 진행성 NSCLC에서의 Chemo-immunotherapy 효능, 재절제 가능한 NSCLC에서 Neoadjuvant immunotherapy의 병리적 반응(pCR, MPR) 및 생존 이점, 그리고 Stage III NSCLC에서 Durvalumab consolidation therapy의 Real-world evidence에 맞춰져 있다. 또한, AJCC 8th Edition을 중심으로 한 정밀의학 기반의 병기 분류 진화, PD-L1 assay 간 비교 가능성, 그리고 종양 미세환경(TME)과 면역 반응 기전에 대한 이해가 심화되고 있음을 확인하였다. 전반적으로 임상 시험 데이터와 Real-world data 간의 일치성 검증 및 치료 중단 요인 분석이 중요한 연구 흐름으로 부각된다.

주요 주제

NSCLC First-line 및 Adjuvant/Consolidation 치료 전략 EGFR/ALK wild-type, PD-L1 TPS ≥ 1%인 진행성 NSCLC 환자에서 Pembrolizumab plus chemotherapy(P-combo)는 Pembrolizumab monotherapy 대비 Median OS(31.8 vs 20.7개월)와 Median PFS(12.5 vs 7.0개월)에서 통계적으로 유의미한 우위를 보였으며, 특히 PD-L1 TPS 1–49%, 연령 <75세, ECOG-PS 0–1 환자군에서 이득이 확인되었다 [1]. 전이성 NSCLC에서 KEYNOTE-189는 Pembrolizumab plus chemotherapy가 Placebo 병용군 대비 OS와 PFS를 유의하게 연장시켰으며, 이는 PD-L1 발현 수준과 무관하였다 [19]. 반면, IMpower110은 PD-L1 고발현 군에서 Atezolizumab monotherapy가 Platinum-based chemotherapy 대비 Median OS를 향상시켰음을 보였다 [27]. Stage III unresectable NSCLC에서 Definitive chemoradiotherapy 후 Durvalumab consolidation 요법을 받은 환자 중 질병 진행 시 Chemo-immunotherapy를 시행한 군이 Platinum-based chemotherapy 단독군보다 긴 Sub-PFS(12.0개월)를 보였으며, Durvalumab을 12개월 이상 완료한 환자에서 이득이 두드러졌다 [13]. Real-world data(SPOTLIGHT cohort, VHA nationwide study 등)는 PACIFIC trial 이후 Standard-of-care로 자리 잡은 Durvalumab consolidation therapy가 실제 임상에서도 높은 12-month OS rate(약 90%)를 유지하지만, Treatment initiation delay(TID), Treatment interruption(TI), 조기 Discontinuation 등의 문제가 존재함을 확인하였다 [49], [50], [54]. 한국 Real-world data(PACIFIC-KR) 분석에서 CRT 후 Durvalumab consolidation therapy를 받은 환자의 Median rwPFS는 25.9개월로, PACIFIC trial 결과와 유사하거나 더 양호하였다 [58].

Neoadjuvant Immunotherapy의 효능 및 반응 예측 CheckMate 816 trial은 Resectable stage IB (≥4 cm) to IIIA NSCLC 환자에서 Neoadjuvant nivolumab plus platinum-based chemotherapy가 Chemotherapy alone 대비 Event-free survival(EFS)과 Pathological complete response(pCR)을 유의하게 개선함을 입증하였으며, 5-year OS는 실험군 65.4%, 대조군 55.0%로 지속적 생존 이점을 확인하였다 [17], [18]. Neoadjuvant setting에서 Immune checkpoint inhibitors(ICIs)를 투여하면 원발 종양과 Tumor-draining lymph nodes(tdLN) 제거 전 항원 제시와 T cell priming이 최대화되어 Adjuvant therapy보다 더 다양하고 지속적인 면역 반응을 유도한다 [6]. NeoR-World 연구라는 대규모 다기관 Real-world cohort study에서 Resectable NSCLC 환자에게 시행된 Neoadjuvant immunochemotherapy는 Chemotherapy alone 대비 pCR, DFS, OS에서 유의미한 우위를 보였으며, 특히 Lung squamous cell carcinoma 환자에서 더 높은 Pathologic response를 나타냈다 [90]. Stage IB–IIIB Lung squamous cell carcinoma(LUSC) 환자에서 Neoadjuvant immunochemotherapy는 Chemotherapy 대비 Major pathologic response(MPR) 및 pCR에서 유의하게 높은 반응률을 보였다 [44]. 그러나 Resectable NSCLC 환자에서 Neoadjuvant-adjuvant PD-1/PD-L1 inhibitor 요법이 Neoadjuvant-only 요법보다 우월한지 비교한 Indirect meta-analysis 결과, Adjuvant phase에 Immunotherapy를 추가하는 것이 EFS나 OS에서 통계적으로 유의미한 차이를 보이지 않는 것으로 나타났다 [92].

병기 분류의 진화 및 예후 바이오마커 AJCC Cancer Staging Manual 제8판은 기존 인구 집단 기반 TNM 분류에서 분자생물학적 마커와 비해부학적 요소를 통합한 Personalized approach로 전환하며, HPV 상태에 따른 구인두암 별도 병기 체계 도입 및 Neoadjuvant therapy를 받은 식도/위암 환자 분류 변경 등 Precision molecular oncology 시대에 부합하는 Prognostic stage groups을 정의하였다 [3], [4]. IASLC Lung Cancer Staging Project는 Recursive partitioning and amalgamation algorithm을 활용하여 Tumor size 기준 세분화 및 T3/T4 경계 재정의의 통계적 타당성을 검증했다 [21]. Head and neck squamous cell carcinoma(HNSCC)에서 Pathological Extranodal Extension(pENE)는 Aggressive tumor phenotype, Locoregional recurrence, Distant metastasis 및 Reduced Overall survival(OS)과 연관된 핵심 Prognostic biomarker이며, AJCC 8th edition 및 UICC 9th edition(2025)의 병기 체계 변경 배경이 되나, HPV-positive oropharyngeal carcinoma(OPSCC)에서의 예후적 의미는 여전히 논란의 여지가 있다 [12]. Radiological N0 상태의 NSCLC 환자에서 Occult mediastinal metastasis(N2 disease)를 가장 잘 예측하는 Central tumour 정의는 Midline 기점 Concentric lines를 이용한 Hemithorax inner one-third 기준임이 확인되었다 [73].

면역치료 관련 부작용, 저항성 및 종양 미세환경(TME) NSCLC 환자에서 Immune checkpoint inhibitor(ICI) 치료 중 발생하는 Hyperprogressive Disease(HYD)의 정의가 TGR, TGK, RECIST 1.1 기반 크기 증가율 등 혼재되어 발생률 편차가 크며(5~37%), Time-dependent criteria 적용을 위한 Pre-baseline imaging 부재가 주요 한계로 지적된다 [8]. Pseudoprogression은 전체 환자의 약 3%로 드물게 발생하여 iRECIST 등 수정된 평가 기준의 일상적 실용성에 의문이 제기되었으나, Hyperprogression은 약 14%로 더 흔하며 조기 사망과 강하게 연관되어 있어 조기 영상 재평가 및 치료 전환이 필요하다 [16]. Squamous NSCLC 환자에서 Nivolumab 치료 중 발생한 Pseudoprogression은 CD8+CD103+ tissue-resident memory T cell의 국소적 침윤 및 증식으로 인한 면역 반응임이 조직검사로 입증되었다 [70]. Unresectable Stage III NSCLC 환자에서 dCCRT 후 Durvalumab 유지치료 중 발생한 Mild immune-related adverse events (irAEs, steroid 미투여)는 Median PFS가 Not reached로 가장 길었으나, Nonmild irAEs(systemic steroid 투여) 발생 시 Median PFS는 9.7개월로 짧아져 irAE의 Severity와 예후 간의 복잡한 연관성을 시사했다 [25]. Baseline derived neutrophil-to-lymphocyte ratio(dNLR)는 CRT 후 Durvalumab 투여 시 Checkpoint inhibitor-related pneumonitis(CIP) 및 irAEs의 안전성 예측 Biomarker로 활용 가능함 [78].

EGFR-mutant NSCLC 및 Transformed SCLC ESMO 가이드라인은 ADAURA trial 결과를 근거로 Stage IB-IIIA NSCLC 중 EGFR exon 19 deletion 또는 exon 21 L858R mutation이 있는 완전 절제 환자에서 Adjuvant osimertinib 사용을 권고한다 [66]. NCCN 가이드라인(Version 4.2024/2026)은 Driver mutation 양성 환자에서 PD-L1 수치와 무관하게 First-line targeted therapy를 우선 권장하며, EGFR exon 19 deletion 또는 exon 21 L858R mutation 환자에서 Osimertinib monotherapy를 표준으로 제시한다 [68], [69]. 진행성 NSCLC 환자 중 EGFR 변이와 동시 TP53 변이를 가진 고위험군에서, 1차 치료로 Osimertinib 단독 요법 대비 Osimertinib 기반 화학요법 병용 요법이 Median PFS를 15.6개월에서 34.0개월로 유의하게 연장시켰다(HR 0.44; P < .001) [85]. Stage III EGFR-mutated NSCLC 환자에서 Definitive chemoradiotherapy 이후 Osimertinib 투여 시 Median PFS가 Placebo군(5.6개월) 대비 39.1개월로 유의하게 우월함을 보인 LAURA trial 결과가 보고되었다 [46]. 반면, PACIFIC trial의 Post hoc subgroup analysis에서는 EGFR-mutant 환자에서 Consolidation durvalumab의 PFS 이점이 명확하지 않음을(HR 0.91) 시사하였다 [51]. EGFR-TKI 치료 후 소세포폐암으로 변이된 Transformed SCLC(T-SCLC)와 Primary SCLC(P-SCLC)를 비교한 결과, T-SCLC 군의 Median OS(11.7개월)가 P-SCLC 군(12.9개월)보다 짧았으나 임상적 차이는 미미했으며, 두 군 모두에서 Chemoimmunotherapy가 Chemotherapy 대비 OS를 현저히 향상시켰다 [11]. EGFR-mutant lung adenocarcinoma에서 발생한 T-SCLC의 예측 모델은 Age, RB1/NTRK1 mutation, Secondary T790M mutation을 포함하며, 변형까지의 중위 기간은 25.8개월임 [62].

방법론적 경향

연구 설계 및 Cohort 특징 NSCLC 임상시험 생태계에서 University-sponsored trial은 감소한 반면, International multi-center trial 및 Biomarker-based patient selection 비율이 증가하는 경향을 보였다 [77]. Resectable NSCLC 환자에서 Neoadjuvant, Adjuvant, Perioperative immunotherapy-based treatment protocols의 Meta-analysis 결과, Treatment setting에 따라 Therapy omission rate 및 Grade ≥ 3 AEs 발생률이 현저히 달랐으며, Neoadjuvant setting에서 Overall protocol compliance가 가장 높았다 [22]. Real-world data 분석은 PACIFIC trial inclusion criteria를 충족하지 못하는 환자군에서도 Durvalumab consolidation therapy의 효능을 확인하는 데 중요하게 활용되었다 [35].

Endpoint 및 평가 기준 Neoadjuvant immunotherapy 후 Major pathological response(MPR) 예측을 위해 Dynamic 18F-FDG PET/CT를 활용했을 때, SUVmax 감소율이 MPR과 독립적으로 연관되었으며, ROC curve analysis를 통해 MPR 예측의 최적 임계값은 SUVmax 감소 60%로 도출되었다 [10]. Primary tumor (PT) 및 Lymph nodes (LNs)에서의 Residual viable tumor (RVT) 비율이 EFS를 예측하는 강력한 Surrogate endpoint임이 규명되어, 기존 이진적 기준(pCR/MPR)보다 정량적 평가의 유용성이 강조되었다 [15]. 고형암의 Tumor response assessment에서 Morphologic criteria(RECIST)와 Metabolic criteria(EORTC, PERCIST) 간 일치도는 Moderate 수준이며, Overall response rate(ORR) 차이 분석을 통해 각 기준의 특성을 비교하였다 [37]. Immune checkpoint inhibitors(ICPIs) 치료 중 나타나는 Pseudoprogression, Dissociated response 등 Atypical response patterns에 대해 기존 PERCIST 기준의 한계를 보완하는 wsPERCIST 판독 기준이 제안되었다 [47].

Biomarker 및 Assay 표준화 PD-L1은 Pembrolizumab 치료의 Clinical benefit을 예측하는 중요한 Biomarker로, 특히 PD-L1 proportion score ≥50% 환자군에서 Objective response rate(ORR)이 현저히 높았다 [20]. 그러나 네 가지 주요 PD-L1 IHC assay (22C3, 28-8, SP142, SP263) 간의 비교 연구에서는 Tumor cell (TC) 염색 패턴의 유사성에도 불구하고, SP142 assay가 다른 assay들에 비해 상대적으로 적은 수의 양성 TC를 검출하는 차이가 확인되었다 [28]. Advanced NSCLC에서 PD-L1 inhibitors 치료 결정을 위한 PD-L1 IHC assays 간 비교 가능성(comparability)을 평가한 결과, 22C3, 28-8, SP263은 높은 일치도를 보였으나 SP142는 상대적으로 낮은 Concordance를 나타냈다 [38]. Circulating tumor antigen (ctA) 패널과 Machine learning(XGBoost) 모델의 결합은 전이성 NSCLC First-line treatment 중 Overall survival(OS) 예측에 추가적인 Prognostic value를 제공함 [84].

통계적 방법 및 AI 적용 Stage III NSCLC 환자에서 Adjuvant Durvalumab의 최적 치료 기간에 대한 연구에서, 실제 임상에서의 높은 중단률과 독성 부담을 고려하여 Treatment duration de-escalation(6개월, 9개월 vs 12개월)의 타당성을 Marginal structural model 및 Time-dependent Cox regression으로 평가함 [9]. AI 기반 WSI 분석 도구(Lunit SCOPE IO)는 H&E 염색 슬라이드에서 CE, CS, TIL을 자동 분할하여 Immune phenotype(IP: inflamed, immune-excluded, immune-desert)을 정의하며, Inflamed IP는 높은 Tumor response rate 및 연장된 PFS/OS와 연관됨 [57]. Chest CT 기반 Deep learning 모델(ShuffleNetV2x05)은 Tumour proliferation pathway downregulation 및 Antitumour immunity와 연관되어 Neoadjuvant chemoimmunotherapy 후 MPR을 예측하는 데 유용함 [72]. Early-stage NSCLC 환자에서 Neoadjuvant pembrolizumab monotherapy의 치료 반응 예측을 위해 기존 Frequency-based 분석의 한계를 극복하기 위해 Wasserstein distance를 적용한 Distribution-based computational framework(cytoDE)를 제안하였으며, 이 새로운 접근법이 Baseline PBMC 및 절제된 종양 표본에서 Major pathologic response를 더 잘 예측할 수 있음을 보였다 [91].

임상적·연구적 시사점

치료 전략의 정교화 및 개인화 EGFR/ALK wild-type 진행성 NSCLC에서 Chemo-immunotherapy는 표준 치료로 자리 잡았으나, PD-L1 발현 수준, 연령, ECOG-PS 등 하위 집단별 이득 차이를 고려한 환자 선택이 중요하다 [1]. Stage III NSCLC에서 Durvalumab consolidation therapy의 Real-world efficacy는 확인되었으나, Treatment initiation delay 및 조기 Discontinuation 문제를 해결하기 위한 관리 전략이 필요하다 [49], [50], [54]. EGFR-mutant NSCLC에서는 Adjuvant osimertinib가 표준으로 권고되나, Stage III unresectable 환자에서 Consolidation therapy의 선택(Osimertinib vs Durvalumab)은 임상적 상황과 Trial 결과(LAURA vs PACIFIC subgroup)를 종합적으로 고려해야 한다 [46], [51], [66].

면역치료 반응 평가 및 부작용 관리 Pseudoprogression과 Hyperprogression의 정확한 감별 진단이 중요하며, 특히 Hyperprogression은 조기 사망과 강하게 연관되어 있어 조기 영상 재평가 및 치료 전환이 필수적이다 [8], [16]. Immune-related adverse events(irAEs)의 Severity와 예후 간의 복잡한 연관성(Mild irAEs는 긴 PFS, Nonmild irAEs는 짧은 PFS)을 고려하여 부작용 관리 전략을 수립해야 한다 [25]. Radiation pneumonitis 발생 위험을 평가하기 위해 Baseline dNLR 및 Radiation dosimetry 파라미터(V65–45%)를 활용할 수 있다 [76], [78].

Biomarker의 한계와 새로운 접근법 PD-L1 assay 간 비교 가능성 문제는 여전히 존재하며, SP142 assay의 낮은 Concordance를 고려하여 검사 선택 시 주의가 필요하다 [28], [38]. Intratumor Heterogeneity (ITH)로 인한 Sampling bias가 TMB 및 PD-L1 등 Biomarker의 예측력을 제한하는 핵심 요인으로 지적되었다 [88]. 이를 극복하기 위해 Liquid biopsy(ctDNA), Gut microbiota, TCR 레퍼토리 시퀀싱 등 다양한 차원의 Biomarker가 검토되고 있으며, 특히 ctDNA 모니터링이 기존 단일 지표보다 우수한 예측력을 보일 수 있음이 제시되었다 [87]. AI 기반 공간 분석 및 Deep learning 모델은 병리적 반응(MPR) 예측 및 종양 미세환경(TME) 평가에 유용한 도구로 부상하고 있다 [57], [72], [91].

남은 Gap 및 향후 방향 Neoadjuvant immunotherapy의 장기적 생존 이점과 Adjuvant phase 추가 투여의 효용성에 대한 명확한 결론이 아직 부족하며, Indirect meta-analysis 결과 Adjuvant phase 추가가 통계적으로 유의미한 차이를 보이지 않음을 시사한다 [92]. Occult lymph node disease 및 Radiologic extranodal extension(ENE)와 같은 미세 전이 및 림프절 전이의 예후적 의미를 정량화하고, 이를 병기 분류에 어떻게 통합할지에 대한 논의가 계속되어야 한다 [29], [31], [32]. 또한, Transformed SCLC(T-SCLC)와 Primary SCLC(P-SCLC)의 임상적 유사성에도 불구하고, T-SCLC의 예측 모델 개발 및 Chemoimmunotherapy의 효능을 지속적으로 모니터링할 필요가 있다 [11], [62].

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