Spontaneous Regression of Small Cell Lung Cancer: A Case Report

Nakamura N,Hori T,Sekiguchi K,Nishimura N,Suzuki K,Kunishima N,Matsusako M

doi:10.4172/2165-7920.10001105

Abstract

Spontaneous regression (SR) is extremely rare in small cell lung cancer (SCLC). The present study reports a rare case of SCLC accompanied by partial SR in a 68-year-old man. The patient was scheduled to receive chemoradiotherapy for SCLC. Computed tomography (CT) simulation images for radiotherapy revealed partial regression of the primary tumor, while lymph node metastasis progression was observed. On 18F-fluorodeoxyglucose (FDG) positron emission tomography/CT, an abnormally high uptake of FDG was not observed in the primary exhibiting SR, while an extremely high uptake was identified in the lymph node metastases. The patient also presented with bilateral double vision, which suggested neurological paraneoplastic syndrome. He received chemoradiotherapy and a complete response was obtained. Until the last follow-up (58 months since the initiation of chemoradiotherapy), the patient was free from tumor progression.

Highlights

Spontaneous regression (SR) of cancer is defined as the partial or complete, transient or permanent disappearance of a malignant tumor without the administration of any medical treatment [1]
The present study reports a rare case of small cell lung cancer (SCLC) accompanied by partial SR
The patient was clinically diagnosed with double SCLC with ipsilateral hilar and mediastinal lymph node metastases and squamous cell carcinoma [11]

Summary

Introduction

Spontaneous regression (SR) of cancer is defined as the partial or complete, transient or permanent disappearance of a malignant tumor without the administration of any medical treatment [1]. SR is extremely rare in small cell lung cancer (SCLC), with ∼ten reported cases [2-8]. Cytological examination following transbronchial lung biopsy performed on December 12, 2008 diagnosed the left upper lobe nodule as squamous cell carcinoma, and the left lower lobe nodule as SCLC (Figure 2).

Results

Conclusion