Abstract
Background
The prognostic implications of palliative chemotherapy for advanced or recurrent thymic carcinomas require full elucidation. The lung immune prognostic index (LIPI) is a novel prognostic index whose effectiveness has recently been reported in lung cancer patients. This study aimed to evaluate the clinical value of the LIPI in advanced or recurrent thymic carcinoma patients.
Methods
We retrospectively analyzed 41 advanced or recurrent thymic carcinoma patients undergoing palliative chemotherapy between January 2001 and December 2020. Survival‐time analysis was conducted using the Kaplan–Meier method and log‐rank test. Multivariate analysis using the Cox proportional hazards model was performed to investigate the predictive and/or prognostic value of the LIPI.
Results
Median progression‐free survival (PFS) for first‐line chemotherapy and overall survival (OS) were significantly longer in the good‐LIPI group (LIPI: 0) than in the intermediate/poor‐LIPI group (LIPI: 1 or 2) (PFS: 13.4 vs. 6.8 months, p = 0.025; OS: 48.2 vs. 28.9 months, p = 0.00506). Multivariate analysis revealed that intermediate/poor LIPI was the adverse prognostic factor for PFS. With regard to OS, serum albumin <3.5 g/dl and an intermediate/poor LIPI were identified as independent adverse prognostic factors.
Conclusions
Our study indicates that the LIPI is a potential prognostic marker in patients with advanced or recurrent thymic carcinoma undergoing palliative chemotherapy.
Keywords: derived NLR, lactate dehydrogenase, lung immune prognostic index, prognostic marker, thymic carcinoma
In patients with advanced thymic carcinoma undergoing palliative‐intent chemotherapy, the LIPI has a potential prognostic role. Survival time comparison according LIPI score revealed that OS and PFS were significantly long in the good LIPI group.

INTRODUCTION
Thymic carcinomas are rare neoplasms that arise in the anterior mediastinum, with a reported annual incidence of 0.29 per 100 000 population in Japan. 1 Thymic carcinoma is a highly progressive disease characterized by a poor survival rate, local invasion, and distant metastases often present at the time of diagnosis. 2 , 3 Patients with advanced (stage IVa and IVb according to the Masaoka–Koga stage classification) or recurrent thymic carcinoma are usually treated with palliative intent chemotherapy or radiotherapy. However, due to the rarity of this patient population, the optimal chemotherapeutic strategy and sequence of treatment are debatable. Thus, there are conflicting findings in previous reports regarding the prognostic implications of palliative intent chemotherapy for patients with advanced and/or recurrent thymic carcinoma.
Inflammatory dynamics in the tumor microenvironment play a key role in carcinogenesis. 4 In recent years, the prognostic utility of hematological and biochemical parameters that can be routinely evaluated in daily clinical practice and that potentially reflect tumor inflammation have been validated. Typically, the neutrophil‐to‐lymphocyte ratio (NLR) and derived NLR (dNLR), comprising leukocyte fractions, are commonly used parameters. 5 , 6 In cancer patients, these parameters have been reported to act as predictive and/or prognostic biomarkers, indicating tumor inflammatory status reflected by alterations in peripheral blood leukocytes. 6 In addition, other types of clinical parameters such as prognostic nutrition index, 7 C‐reactive protein (CRP) ‐to‐albumin ratio (CAR) 8 have been reported to have prognostic value in various cancers. Furthermore, serum lactate dehydrogenase (LDH) is a well‐known prognostic marker for various types of cancer. Elevated LDH levels have been reported to reflect tumor inflammation 9 and significant tumor growth potential. 10 Based on these perspectives, Mezquita et al. proposed the lung immune prognostic index (LIPI), a composite index comprising the dNLR and LDH, and demonstrated its prognostic and predictive value in non‐small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs). 11 Since then, numerous reports on the clinical utility of the LIPI, especially in lung cancer, have been published. 12 , 13 However, the clinical value of the LIPI in thymic carcinoma remains uncertain, and its prognostic role is unclear. Therefore, we conducted this study to validate the clinical value of the LIPI in patients with advanced or recurrent thymic carcinoma undergoing palliative intent chemotherapy.
METHODS
Patients and setting
The present study was conducted retrospectively at a single institution. Analysis data were collected from paper‐based or electronic medical records. We extracted data on patients diagnosed with thymic carcinoma at our institute between January 2001 and December 2020. Patients meeting the following criteria were included: histopathological diagnosis of thymic carcinoma based on the 2015 World Health Organization classification of thymic tumors, 14 unresectable and advanced‐stage (Masaoka–Koga stage IVa or IVb) carcinoma or postoperative recurrence thereof, receiving at least one regimen of systemic chemotherapy with cytotoxic agents, and not receiving curative treatment other than chemotherapy (i.e., curative intent radiotherapy, salvage surgery, etc.).
Data collection
Data on patient characteristics included age, sex, smoking history, histology, and clinical stage according to the Masaoka–Koga stage classification for thymic tumors, metastatic lesions, and PS as evaluated by the Eastern Cooperative Oncology Group. The laboratory data measured at the initiation of first‐line chemotherapy included serum Alb and CRP to evaluate CAR; peripheral complete blood count, including absolute neutrophil count (ANC) and absolute lymphocyte count (ALC) to calculate the NLR and dNLR; and serum LDH to evaluate the LIPI. NLR was calculated as the ratio of ANC to ALC. CAR was calculated as the ratio of CRP to Alb. The LIPI was evaluated according to the dNLR (ANC/[WBC−ALC]) and serum LDH levels, with scores ranging from 0 to 2 and calculated as follows: dNLR <3 and LDH <223 U/l = 0, dNLR ≥3 and LDH <223 U/l or dNLR <3 and LDH ≥223 U/l = 1, and dNLR ≥3 and LDH ≥223 U/l = 2. The median values of NLR and CAR were employed as cutoff values for univariate and multivariate analysis (NLR: 3.7, CAR: 0.22). In this study, the patients were divided into the following two groups according their LIPI scores: the “good‐LIPI group,” including patients with an LIPI score of 0, and “intermediate/poor‐LIPI group,” including those with LIPI scores of 1 or 2. Regarding clinical course, data on the types of first‐line chemotherapy regimen, treatment response, palliative intent radiotherapy, and survival time were collected. The treatment response for first‐line chemotherapy was evaluated according to the revised Response Evaluation Criteria in Solid Tumors guidelines (v.1.1). 15 The response evaluation was performed by computed tomography scans and/or 18F‐fluorodeoxyglucose‐positron emission tomography according to the discretion of the first physician. The radiological images of all patients were reviewed by two expert pulmonologists (TA and KT, with 10 and 16 years of experience, respectively) to evaluate treatment response and disease progression. Accordingly, ORR, the ratio of patients with complete remission (CR) and partial response (PR) to all patients, and DCR, the ratio of patients with CR, PR and stable disease to all patients were recorded. OS was defined as the period from initiation of chemotherapy to either a fatal event or censored observation. PFS for first‐line chemotherapy was defined as the period from initiation of first‐line chemotherapy to death or disease progression.
Statistical analysis
Kaplan–Meier analysis was performed to plot the PFS and OS curves, and the log‐rank test was employed for intergroup comparisons of PFS and OS. A Cox proportional hazards model was used to identify the prognostic factors for PFS and OS, with statistically significant variables used for the univariate model and clinically important variables further analyzed using multivariate analysis. All statistical analyses were performed using EZR (Saitama Medical Center, Jichi Medical University, Saitama, Japan), a graphical user interface for R (R Foundation for Statistical Computing, Vienna, Austria), and statistical significance was set at p < 0.05. 16
RESULTS
Patient characteristics
During the study period, data on 54 patients with thymic carcinomas were collected from their medical records. Ten patients with insufficient clinical data for analysis and three who had been administered curative treatment, including radiotherapy or salvage thoracic surgery, were excluded; therefore, a total of 41 eligible patients were enrolled. The patient characteristics are presented in Table 1. The median age was 66 years (range: 35–79 years), with 27 (65.9%) men and 14 (34.1%) women. Squamous cell carcinoma was the most common histological type (85.4%). According to the Masaoka–Koga stage classification, 12 (29.3%) and 21 (51.2%) patients were classified as stage IVa and IVb, respectively. Regarding the locations of metastatic sites, serosal metastasis was the most prevalent (46.3%), followed by bone and lung metastases (22% each). A total of 18 (43.9%) patients presented multiple metastatic lesions at the time of diagnosis. Regarding laboratory test values, the mean albumin (Alb), CRP, CAR, NLR, dNLR, and LDH values were 3.8 ± 0.5 g/dl, 2.3 ± 3.4 mg/dl, 0.7 ± 1.1, 4.5 ± 2.6, 2.8 ± 1.5, and 266 ± 133 U/ml, respectively. LIPI scores of 0, 1, and 2 were present in 13 (31.7%), 20 (48.8%), and eight (19.5%) patients, respectively. Comparisons of patient characteristics according to LIPI score are presented in Table 2. The intermediate/poor‐LIPI group exhibited a higher prevalence of poor performance status (PS) scores of 2 or 3 (good LIPI vs. intermediate/poor LIPI: 15.4% vs. 28.6%), bone metastasis (7.7% vs. 28.6%), and presented more metastatic sites (38.5% vs. 46.4%) than the good‐LIPI group; however, none of these differences was statistically significant. Anthracycline with platinum‐based chemotherapy was the most frequently administered first‐line chemotherapy both in good and intermediate/poor LIPI group (84.6% vs. 89.1%), followed by platinum doublet chemotherapy (15.4% vs. 7.1%). Objective response rate (ORR) and disease control rate (DCR) were slightly higher in the good‐LIPI group but not with significant difference. In addition, 30.7% of good‐LIPI patients and 28.6% of intermediate/poor‐LIPI patients received palliative radiotherapy during their clinical course.
TABLE 1.
Patient characteristics (N = 41)
| Variables | n | % | |
|---|---|---|---|
| Age, years, median (range) | 66 (35–79) | ||
| Sex | Male | 27 | 65.9 |
| Female | 14 | 34.1 | |
| Smoking history | Current or former | 22 | 53.7 |
| ECOG‐PS | 0–1 | 31 | 75.6 |
| 2–3 | 10 | 24.4 | |
| Histology | Squamous cell carcinoma | 35 | 85.4 |
| LCNEC | 1 | 2.4 | |
| Undifferentiated carcinoma | 5 | 12.2 | |
| Tumor stage | IVa | 12 | 29.3 |
| IVb | 21 | 51.2 | |
| Post‐ope. | 8 | 19.5 | |
| Metastatic location | Serosal | 19 | 46.3 |
| Bone | 9 | 22 | |
| Lung | 9 | 22 | |
| Lymph node | 6 | 14.6 | |
| Liver | 6 | 14.6 | |
| No. of metastatic sites | 1 | 23 | 56.1 |
| ≥2 | 18 | 43.9 | |
| Laboratory test results, mean ± SD | Alb, g/dl | 3.8 ± 0.5 | |
| CRP, mg/dl | 2.3 ± 3.4 | ||
| CAR | 0.7 ± 1.1 | ||
| NLR | 4.5 ± 2.6 | ||
| dNLR | 2.8 ± 1.5 | ||
| LDH, U/ml | 266 ± 133 | ||
| LIPI | 0 | 13 | 31.7 |
| 1 | 20 | 48.8 | |
| 2 | 8 | 19.5 | |
| No. of treatment lines, median (range) | 2 (1–10) | ||
| PFS, months, median (95% CI) | 7.6 (6.5–11.3) | ||
| OS, months, median (95% CI) | 34.9 (23.9–41.6) | ||
Abbreviations: ECOG‐PS, Eastern Cooperative Oncology Group Performance Status; LCNEC, large cell neuroendocrine carcinoma; Alb, albumin; CRP, C‐reactive protein; CAR, CRP‐to‐albumin ratio; NLR, neutrophil‐to‐lymphocyte ratio; dNLR, derived neutrophil‐to‐lymphocyte ratio; LDH, lactate dehydrogenase; LIPI, lung immune prognostic index; PFS, progression‐free survival; OS, overall survival; CI, confidence interval.
TABLE 2.
Comparison according to LIPI score
| Good LIPILIPI: 0 | Intermediate/poor LIPILIPI: 1–2 | p‐value | ||
|---|---|---|---|---|
| n | N (%) | 13 (%) | 28 (%) | |
| Age, years, median (range) | 65.5 (35–79) | 65.5 (36–79) | 0.483 | |
| Sex | Male | 10 (76.9) | 17 (60.7) | 0.482 |
| Female | 3 (23.1) | 11 (39.3) | ||
| ECOG‐PS | 0–1 | 11 (84.6) | 20 (71.4) | 0.458 |
| 2–3 | 2 (15.4) | 8 (28.6) | ||
| Histology | Squamous cell carcinoma | 12 (92.3) | 22 (78.6) | 0.399 |
| Other | 1 (7.7) | 6 (21.4) | ||
| Tumor stage | IVa | 2 (15.4) | 10 (35.7) | 0.276 |
| IVb | 6 (46.1) | 15 (53.6) | 0.744 | |
| Post‐ope. | 5 (38.5) | 3 (10.7) | 0.084 | |
| Metastatic location | Serosal | 5 (38.5) | 14 (50) | 0.524 |
| Liver | 2 (15.4) | 4 (14.3) | 1.00 | |
| Bone | 1 (7.7) | 8 (28.6) | 0.228 | |
| Lymph node | 4 (30.8) | 2 (7.1) | 0.0685 | |
| Lung | 4 (30.8) | 5 (17.9) | 0.429 | |
| No. of metastatic sites | 1 | 8 (61.5) | 15 (53.6) | 0.742 |
| ≥2 | 5 (38.5) | 13 (46.4) | ||
| First‐line regimen | Platinum with anthracycline | 11 (84.6) | 25 (89.3) | 0.645 |
| Platinum doublet | 2 (15.4) | 2 (7.1) | 0.58 | |
| Monotherapy | 0 (0) | 1 (3.6) | 1.00 | |
| Response to first‐line treatment | PR | 7 | 14 | |
| SD | 5 | 9 | ||
| PD | 1 | 2 | ||
| NE | 0 | 3 | ||
| ORR, % (95% CI) | 53.8 (25.1–80.8) | 50 (30.6–69.4) | 1.00 | |
| DCR, % (95% CI) | 92.3 (64–99.8) | 82.1 (63.1–93.9) | 0.645 | |
| Survival time, months, median (95% CI) | PFS | 13.4 (6.3–18.9) | 6.8 (5.8–8.4) | |
| OS | 48.2 (25.3–NA) | 28.9 (10.4–35.6) | ||
| No. of treatment lines, median (range) | 2 (1–6) | 2 (1–10) | ||
Abbreviations: CI, confidence interval; LIPI, lung immune prognostic index; Alb, albumin; PR, partial response; SD, stable disease; PD; progressive disease; NE, not evaluated; ORR, objective response rate; DCR, disease control rate; PFS, progression‐free survival; OS, overall survival; NA, not applicable.
Survival‐time analysis
Median progression free survival (PFS) and overall survival (OS) were 7.6 months (95% confidence interval [CI]: 6.5–11.3) and 34.9 months (95% CI: 23.9–41.6), respectively (Figure 1). PFS and OS were both superior in the good‐LIPI group (good LIPI vs. intermediate/poor LIPI: PFS, 13.4 vs. 6.8 months, p = 0.025; OS, 48.2 vs. 28.9 months, p = 0.00506; Figure 2).
FIGURE 1.

Kaplan–Meier curves of (a) overall survival and (b) progression‐free survival in all patients
FIGURE 2.

Kaplan–Meier curves of (a) overall survival and (b) progression‐free survival stratified by LIPI score. The black line represents the good‐LIPI group and the red line the intermediate/poor‐LIPI group
Prognostic factors for PFS and OS
The results of univariate and multivariate analyses of PFS and OS using the Cox proportional hazards model are presented in Tables 3 and 4, respectively. Univariate analysis revealed an association between an intermediate/poor LIPI and inferior PFS (hazard ratio [HR] = 2.39, p = 0.0285); moreover, an intermediate/poor LIPI was also an independent prognostic factor in multivariate analysis (HR = 2.6, 95% CI: 1.15–5.89, p = 0.0216). In univariate analysis of OS, two or more metastatic sites (HR = 2.16, p = 0.043), Alb <3.5 g/dl (HR = 2.85, p = 0.00977), and an intermediate/poor LIPI (HR = 3.41, p = 0.008) were associated with inferior OS. Multivariate analysis also revealed that Alb <3.5 g/dL [HR = 2.85, 95% CI: 1.24–6.58, p = 0.0139) and an intermediate/poor LIPI (HR = 2.85, 95% CI: 1.08–7.54, p = 0.0347) were independent prognostic factors for OS.
TABLE 3.
Cox proportional hazards model for PFS
| Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|
| Variables | HR (95% CI) | p‐value | HR (95% CI) | p‐value |
| Age: <65 vs. ≥65 | 0.84 (0.42–1.67) | 0.614 | ||
| Sex: Female vs. male | 1.06 (0.5–2.23) | 0.879 | ||
| ECOG‐PS: 0–1 vs. 2–3 | 0.86 (0.38–1.91) | 0.705 | ||
| Histology: Other vs. SCC | 0.91 (0.35–2.39) | 0.845 | ||
| Stage (Masaoka–Koga): IVa, post‐op. Vs. IVb | 1.18 (0.51–2.74) | 0.695 | ||
| No. of metastatic sites: 1 vs. ≥2 | 1.39 (0.69–2.81) | 0.355 | 1.26 (0.62–2.57) | 0.522 |
| NLR: ≤3.7 vs. >3.7 | 1.48 (0.75–2.93) | 0.255 | ||
| Alb: ≥3.5 vs. <3.5 | 0.93 (0.43–1.99) | 0.846 | 0.67 (0.3–1.49) | 0.522 |
| CAR: ≤0.22 vs. >0.22 | 1.23 (0.61–2.47) | 0.559 | ||
| LIPI: Good (0) vs. intermediate/poor (1–2) | 2.39 (1.1–5.21) | 0.0285 | 2.6 (1.15–5.89) | 0.0216 |
Abbreviations: PFS, progression‐free survival; HR, hazard ratio; CI, confidence interval; ECOG‐PS, Eastern Cooperative Oncology Group Performance Status; SCC, squamous cell carcinoma; NLR, neutrophil‐to‐lymphocyte ratio; Alb, albumin; CAR, C‐reactive protein‐to‐albumin ratio; LIPI, lung immune prognostic index.
TABLE 4.
Cox proportional hazards model for OS
| Univariate analysis | Multivariate analysis | |||
|---|---|---|---|---|
| Variables | HR (95% CI) | p‐value | HR (95% CI) | p‐value |
| Age: <65 vs. ≥65 | 0.96 (0.45–2.01) | 0.904 | ||
| Sex: Female vs. male | 0.54 (0.25–1.14) | 0.106 | ||
| ECOG‐PS: 0–1 vs. 2–3 | 1.60 (0.72–3.53) | 0.247 | ||
| Histology: Other vs. SCC | 0.89 (0.36–2.21) | 0.803 | ||
| Stage (Masaoka–Koga): IVa, post‐op. vs. IVb | 1.17 (0.56–2.43) | 0.682 | ||
| No. of metastatic sites: 1 vs. ≥2 | 2.16 (1.03–4.53) | 0.043 | 1.74 (0.78–3.85) | 0.174 |
| NLR: ≤3.7 vs. >3.7 | 1.59 (0.8–3.16) | 0.188 | ||
| Alb: ≥3.5 vs. <3.5 | 2.85 (1.29–6.29) | 0.00977 | 2.85 (1.24–6.58) | 0.0139 |
| CAR: ≤0.22 vs. >0.22 | 0.92 (0.44–1.91) | 0.819 | ||
| LIPI: Good (0) vs. intermediate/poor (1–2) | 3.41 (1.38–8.46) | 0.008 | 2.85 (1.08–7.54) | 0.0347 |
Abbreviations: OS, overall survival; HR, hazard ratio; CI, confidence interval; ECOG‐PS, Eastern Cooperative Oncology Group Performance Status; SCC, squamous cell carcinoma; NLR, neutrophil‐to‐lymphocyte ratio; Alb, albumin; CAR, C‐reactive protein‐to‐albumin ratio; LIPI, lung immune prognostic index.
DISCUSSION
The present study demonstrated that pretreatment LIPI has prognostic potential for patients with thymic carcinoma treated exclusively with palliative intent chemotherapy. Pretreatment LIPI was also associated with PFS for first‐line chemotherapy. The patients were divided into the following two groups according to LIPI score: the “good‐LIPI group” and “intermediate/poor‐LIPI group,” based on the study by Mezquita et al. 11 In the intermediate/poor‐LIPI group, there were higher rates of poor PS, histological types other than squamous cell carcinoma, and multiple metastatic lesions, and these differences were not statistically significant. In the survival‐time analysis, PFS and OS were both significantly shorter in the intermediate/poor‐LIPI group. In the multivariate analysis for PFS for the first‐line chemotherapy, an intermediate/poor LIPI was an independent adverse prognostic factor. Multivariate analysis for OS revealed that Alb <3.5 g/dl and an intermediate/poor LIPI were independent adverse prognostic factors. Of investigated clinical parameters (NLR, CAR and LIPI), LIPI may have had the superior prognostic potential in this study. To the best of our knowledge, this is the first study to demonstrate the prognostic potential of the LIPI in patients with advanced and metastatic thymic carcinoma.
Recently, a multicenter, retrospective study on advanced thymic carcinoma, involving a comparatively large sample size, was conducted in Japan. 17 , 18 , 19 The results of the study revealed no significant difference in OS between the first‐line chemotherapy regimens, whereas tumor staging (Masaoka–Koga stage IVa) was an independent prognostic factor for OS. 17 , 18 In addition, hypoalbuminemia was identified as an independent prognostic factor. 17 These findings indicate that in patients with advanced or metastatic thymic carcinoma, clinical characteristics and laboratory findings may have prognostic potential superior to that of chemotherapy regimen. Thus, in the present study, we applied the LIPI and evaluated its clinical utility as a novel prognostic marker in patients with thymic carcinoma.
LDH plays an unfavorable role in various cancers; it is reportedly associated with tumor invasion and proliferation, 20 metastatic potential, 21 and drug resistance. 22 Elevated dNLR indicates a preference for granulocytes and monocytes over lymphocytes, reflecting the promotion of inflammatory dynamics in the tumor microenvironment. 6 The LIPI is a novel clinical indicator initially proposed by Mezquita et al., who validated its prognostic value in NSCLC patients treated with ICIs. 11 In their seminal report, it was suggested that LIPI potentially strengthens the prognostic power of LDH and the dNLR and facilitates better stratification of the patient population. Thereafter, its prognostic value was reported not only in ICIs but also in NSCLC patients treated with epidermal growth factor receptor tyrosine kinase inhibitors 13 and cytotoxic chemotherapy 12 as well as in patients with small cell lung cancer. 23 In recent years, the LIPI has been applied not only in lung cancer but also in the analysis of other cancer types. In their retrospective analysis of 361 resected esophageal squamous cell carcinomas, Feng et al. reported that a good LIPI was significantly associated with a superior 5‐year survival rate, and this was observable at any stage of the disease. 24 Daniel et al. retrospectively analyzed 578 solid‐tumor patients, including 145 renal cell carcinoma patients treated with ICIs, and demonstrated that in the renal cell carcinoma cohort, an intermediate/poor LIPI was significantly associated with shorter PFS and OS. 25 Chen et al. also analyzed 108 patients with advanced hepatocellular carcinoma treated with ICIs and found that an intermediate/poor LIPI was significantly associated with a poor disease control rate as well as shorter PFS and OS. 26 To date, the clinical value of the LIPI for advanced thymic carcinoma has not been investigated. Only one observational study suggested that elevated serum LDH is an independent prognostic factor for advanced thymic carcinoma, although, unlike our patient population, it included patients who underwent curative surgical or radiological treatment. 27
Our data revealed that hypoalbuminemia and an intermediate/poor LIPI were significantly associated with unfavorable survival outcomes. Serum albumin is a well‐known prognostic marker for several cancer types. 28 In addition to being a nutritional indicator, albumin also acts as a parameter representing inflammatory dynamics, and it is affected by several factors, such as extracellular fluid volume, dehydration status, and inflammatory dynamics. Our results corroborate those of a previous study by Okuma et al., in which hypoalbuminemia was found to be an adverse prognostic factor for OS in advanced thymic carcinoma. 17 Notably, the present study demonstrated that an intermediate/poor LIPI was an independent negative prognostic factor for both PFS and OS. Although there was no significant difference in response rate according to LIPI score, pretreatment LIPI was associated with longer PFS to first‐line treatment, which might have better stratified subsequent long‐term survival. We believe that, in advanced thymic carcinoma, for which the optimal chemotherapeutic strategy is debatable, the LIPI, an easy stratification tool, may be beneficial in clinical practice.
This study had certain limitations. First, the small sample size and retrospective nature of this study might have influenced patient background and selection. Due to the small sample size, it was difficult to make a comparison between three LIPI groups; that is, good (0), intermediate (1), and poor (2), as in the previous studies. Thus, the results of this study, which was conducted on a small sample size, should be cautiously interpreted. Even though thymic carcinoma is a relatively rare disease, it is challenging to perform prognostic evaluation on a small sample population; the results of the present study lack external validity. Second, in our study, patients who underwent curative radiotherapy or surgical resection during their clinical course were excluded, whereas those who received palliative radiotherapy were included. As the definition of “palliative radiotherapy” is unclear, there might have been selection bias in the process of patient recruitment. Furthermore, we did not examine treatment beyond second‐line chemotherapy; although there is no established strategy for chemotherapy beyond second‐line therapy in advanced thymic carcinoma, the course of post‐treatment may affect OS.
In conclusion, this is the first study to suggest the clinical benefits of the LIPI in the prognosis of advanced or recurrent thymic carcinoma. The results of the present study suggested that LIPI might be superior to Alb, a universal cancer prognostic marker; the intensity of tumor growth reflected by LDH and the inflammatory dynamics in the tumor microenvironment reflected by dNLR could have better stratified the patients.
CONFLICT OF INTEREST
The authors declare no competing interests.
ACKNOWLEDGMENTS
Not applicable.
Araki T, Tateishi K, Komatsu M, Sonehara K, Kanda S, Hanaoka M, et al. Association of lung immune prognostic index with survival outcome in advanced thymic carcinoma patients treated with palliative intent chemotherapy. Thorac Cancer. 2022;13:1006–1013. 10.1111/1759-7714.14349
REFERENCES
- 1. Koizumi T, Otsuki K, Tanaka Y, Noguchi T, Fukushuima T, Kobayashi T, et al. National incidence and initial therapy for thymic carcinoma in Japan: based on analysis of hospital‐based cancer registry data, 2009‐2015. Jpn J Clin Oncol. 2020;50:434–9. 10.1093/jjco/hyz203 [DOI] [PubMed] [Google Scholar]
- 2. Ruffini E, Detterbeck F, Van Raemdonck D, et al. Thymic carcinoma: a cohort study of patients from the European society of thoracic surgeons database. J Thorac Oncol. 2014;4:541–8. 10.1097/JTO.0000000000000128 [DOI] [PubMed] [Google Scholar]
- 3. Petat A, Dansin E, Calcagno F, et al. Treatment strategies for thymic carcinoma in a real‐life setting. Insights from the RYTHMIC network. Eur J Cancer. 2021;162:118–27. 10.1016/j.ejca.2021.11.028 [DOI] [PubMed] [Google Scholar]
- 4. Landskron G, De la Fuente M, Thuwajit P, Thuwajit C, Hermoso MA. Chronic inflammation and cytokines in the tumor microenvironment. J Immunol Res. 2014;2014:149185. 10.1155/2014/149185 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Templeton AJ, McNamara MG, Šeruga B, et al. Prognostic role of neutrophil‐to‐lymphocyte ratio in solid tumors: a systematic review and meta‐analysis. J. Natl Cancer Inst. 2014;106:dju124. 10.1093/jnci/dju124 [DOI] [PubMed] [Google Scholar]
- 6. Capone M, Giannarelli D, Mallardo D, et al. Baseline neutrophil‐to‐lymphocyte ratio (NLR) and derived NLR could predict overall survival in patients with advanced melanoma treated with nivolumab. J. Immunother Cancer. 2018;6:74. 10.1186/s40425-018-0383-1 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7. Buzby GP, Mullen JL, Matthews DC, Hobbs CL, Rosato EF. Prognostic nutritional index in gastrointestinal surgery. Am J Surg. 1980;1:160–7. 10.1016/0002-9610(80)90246-9 [DOI] [PubMed] [Google Scholar]
- 8. Cui X, Jia Z, Chen D, Xu C, Yang P. The prognostic value of the C‐reactive protein to albumin ratio in cancer: an updated meta‐analysis. Medicine. 2020;14:99. 10.1097/MD.0000000000019165 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9. Wang H, Wang MS, Zhou YH, Shi JP, Wang WJ. Prognostic values of LDH and CRP in cervical cancer. Onco Targets Ther. 2020;13:1255–63. 10.2147/OTT.S235027 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10. Gallo M, Sapio L, Spina A, Naviglio D, Calogero A, Naviglio S. Lactic dehydrogenase and cancer: an overview. Front. Biosci. (Landmark Ed.). 2015;20:1234–49. 10.2741/4368 [DOI] [PubMed] [Google Scholar]
- 11. Mezquita L, Auclin E, Ferrara R, Charrier M, Remon J, Planchard D, et al. Association of the Lung Immune Prognostic index with immune checkpoint inhibitor outcomes in patients with advanced non‐small cell lung cancer. JAMA Oncol. 2018;4:351–7. 10.1001/jamaoncol.2017.4771 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Kazandjian D, Gong Y, Keegan P, Pazdur R, Blumenthal GM. Prognostic value of the lung immune prognostic index for patients treated for metastatic non‐small cell lung cancer. JAMA Oncol. 2019;5:1481–5. 10.1001/jamaoncol.2019.1747 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13. Minami S, Ihara S, Komuta K. Pretreatment lung immune prognostic index is a prognostic marker of chemotherapy and epidermal growth factor receptor tyrosine kinase inhibitor. World J. Oncol. 2019;10:35–45. 10.14740/wjon1179 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Marx A, Chan JK, Coindre JM, et al. The 2015 World Health Organization classification of tumors of the thymus: continuity and changes. J Thorac Oncol. 2015;10:1383–95. 10.1097/JTO.0000000000000654 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15. Schwartz LH, Litière S, de Vries E, Ford R, Gwyther S, Mandrekar S, et al. RECIST 1.1‐update and clarification: from the RECIST committee. Eur J Cancer. 2016;62:132–7. 10.1016/j.ejca.2016.03.081 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16. Kanda Y. Investigation of the freely available easy‐to‐use software 'EZR' for medical statistics. Bone Marrow Transplant. 2013;48:452–8. 10.1038/bmt.2012.244 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17. Okuma Y, Ko R, Shukuya T, et al. Prognostic factors for patients with metastatic or recurrent thymic carcinoma receiving palliative‐intent chemotherapy. Lung Cancer. 2020;2020(148):122–8. 10.1016/j.lungcan.2020.08.014 [DOI] [PubMed] [Google Scholar]
- 18. Ko R, Shukuya T, Okuma Y, Tateishi K, Imai H, Iwasawa S, et al. Prognostic factors and efficacy of first‐line chemotherapy in patients with advanced thymic carcinoma: a retrospective analysis of 286 patients from NEJ023 study. Oncologist. 2018;23:1210–7. 10.1634/theoncologist.2017-0586 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. Tateishi K, Ko R, Shukuya T, Okuma Y, Watanabe S, Kuyama S, et al. Clinical outcomes of second‐line chemotherapy in patients with previously treated advanced thymic carcinoma: a retrospective analysis of 191 patients from the NEJ023 study. Oncologist. 2020;25:e668–74. 10.1634/theoncologist.2019-0593 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20. Koukourakis MI, Giatromanolaki A, Sivridis E, Gatter KC, Harris AL. Tumour angiogenesis research group. Lactate dehydrogenase 5 expression in operable colorectal cancer: strong association with survival and activated vascular endothelial growth factor pathway–a report of the tumour angiogenesis research group. J Clin Oncol. 2006;24:4301–8. 10.1200/JCO.2006.05.9501 [DOI] [PubMed] [Google Scholar]
- 21. Jin L, Chun J, Pan C, Alesi GN, Li D, Magliocca KR, et al. Phosphorylation‐mediated activation of LDHA promotes cancer cell invasion and tumour metastasis. Oncogene. 2017;36:3797–806. 10.1038/onc.2017.6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Jin HF, Wang JF, Shao M, Zhou K, Ma X, Lv XP. Down‐regulation of miR‐7 in gastric cancer is associated with elevated LDH‐A expression and chemoresistance to cisplatin. Front Cell Dev Biol. 2020;8:555937. 10.3389/fcell.2020.555937 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23. Sonehara K, Tateishi K, Komatsu M, Yamamoto H, Hanaoka M. Lung immune prognostic index as a prognostic factor in patients with small cell lung cancer. Thorac Cancer. 2020;11:1578–86. 10.1111/1759-7714.13432 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24. Feng JF, Zhao JM, Chen S, Chen QX. Prognostic significance of the lung immune prognostic index in patients with resected esophageal squamous cell carcinoma. Cancer Manag. Res. 2021;13:2811–9. 10.2147/CMAR.S298412 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Meyers DE, Stukalin I, Vallerand IA, Lewinson RT, Suo A, Dean M, et al. The lung immune prognostic index discriminates survival outcomes in patients with solid tumors treated with immune checkpoint inhibitors. Cancer. 2019;11:1713. 10.3390/cancers11111713 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26. Chen S, Huang Z, Jia W, et al. Association of the Pretreatment Lung Immune Prognostic index with survival outcomes in advanced hepatocellular carcinoma patients treated with PD‐1 inhibitors. J Hepatocell Carcinoma. 2020;7:289–99. 10.2147/JHC.S277453 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27. Wu JX, Chen HQ, Shao LD, Qiu SF, Ni QY, Zheng BH, et al. Long‐term follow‐up and prognostic factors for advanced thymic carcinoma. Med (Baltim). 2014;93:e324. 10.1097/MD.0000000000000324 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Gupta D, Lis CG. Pretreatment serum albumin as a predictor of cancer survival: a systematic review of the epidemiological literature. Nutr. J. 2010;9:69. 10.1186/1475-2891-9-69 [DOI] [PMC free article] [PubMed] [Google Scholar]
