Nasopharyngeal carcinoma (NPC) is one of the most common malignant cancers in the east and southeast Asia and is highly sensitive to radiation (1, 2). However, about 10%-15% of patients experience locoregional recurrence after primary treatment (3, 4). For patients with locoregional recurrent nasopharyngeal carcinoma without distant metastasis (lrNPC), treatment strategies are mainly divided into three types: surgery, re-irradiation, and chemotherapy-based comprehensive treatment. Surgery and re-irradiation are limited due to the initial treatment and complex structure of the nasopharynx (5, 6), so chemotherapy-based comprehensive treatment, is a better choice for lrNPC and confers survival benefits by increasing the local control rate and eradicating micrometastases (7).

Accurate prognostic stratification is critical for therapeutic decisions making. Most studies constructed the prognostic stratification models in lrNPC mainly focused on patients treated with surgery or re-irradiation after recurrence, there are few studies on the prognosis prediction of chemotherapy-based comprehensive treatment (8, 9). In addition, doctors make chemotherapy-based comprehensive treatment strategy were based on individualized judgement and patient characteristics, which is short of quantifiable criteria. Therefore, it is necessary to find good prognostic indicators and establish a prognostic stratification model for chemotherapy-based comprehensive treatment.

Inflammation is considered to be cancer-initiating factors and participate in the entire process of cancer development (10). NPC is a well-recognized inflammatory cancer, adding inflammatory factors to the prognostic stratification system can help to improve the sensitivity of prognostic stratification. Among the established cancers, there is increasing evidence that cancer-related inflammation, tumor stage, and clinical condition jointly affect the prognosis of patients (11). The general nutritional condition of the patients with recurrence is worse than before, and many patients are even difficult to receive anti-recurrent treatment due to poor nutritional condition, so the nutritional indicators are critical for lrNPC patients. However, most of these markers were evaluated separately, so we collected as many prognostic biomarkers as possible, assessed the value of these biomarkers, and chose the optimal ones to construct a prognostic stratification model, aiming to refine patient stratification conveniently and efficiently.

In this study, we established a prognostic stratified model for lrNPC to help oncologists make treatment decisions. By applying this model, high-risk patients could increase the treatment intensity, and low-risk patients could reduce the treatment intensity, effectively avoiding over-treatment and under-treatment.

Currently, therapeutic decisions making and prognostic stratification for NPC are based on TNM stage system, and patients are stratified according to the anatomical region. Instead of full consideration of the biological heterogeneity of cancer (15), this is often insufficient for prognostic stratification and individualized treatment. In addition, the stage system of recurrence uses the TNM stage, which is the same system for initial diagnosed NPC, and this would decrease the accuracy of the prognostic stratification (16, 17).For recurrent patients, accurate prognostic stratification and individualized treatment are very important (18, 19). The structure of the nasopharynx has changed after primary treatment, as well as the receptivity to anti-recurrence treatment. This increased the difficulty for clinicians to choose effective treatment measures, and clinicians need to consider the efficacy as well as side effects more carefully. In our study, prognostic factors were identified based on analysis of patients with lrNPC, and individual prognostic risk scores were calculated for risk stratification. The prediction of OS in low-risk group patients was significantly better than that in high-risk group patients, suggesting that our model performed well in prognostic stratification of patients with lrNPC.

Cancer biology is constantly shifting from a “cancer cell-centric” view to a broader concept that places inflammation as a cancer biomarker, the key role of inflammation in carcinogenic process has attracted attention (20), and inflammation is a recognized hallmark of cancer, which greatly promotes the development of cancer (21). Inflammation can affect both the treatment response and prognosis in caners (22–25), and this had been confirmed in many clinical studies of different cancer types (26–32).The study of Leggas M in patients with non-small cell lung cancer proved that intensive anti-inflammatory therapy can improve the efficacy of chemotherapy drugs, reduce blood toxicity, and change the pharmacokinetics of drugs (33). In the past few years, a number of systemic inflammation markers have been used as prognostic predictors, and there are also a lot of studies that have confirmed the value of these indicators in predicting the prognosis of different solid tumors (34–37). Considering the accessibility, ease of use, and economic cost of these markers, 15 common blood-related markers were selected in our study, and through further screening, 2 blood-related prognostic factors were selected to construct the nomogram.

ALB was also added as a prognostic factor in constructing the nomogram in our study. According to the latest studies, ALB is strongly associated with all-cause mortality, including cancer, cardiovascular diseases, and respiratory diseases, and lower ALB is associated with an increased risk of death (38–42). This is further confirmed in all cancer types, The studies in cervical carcinoma and vulvar squamous cell carcinoma had proved the value of nutritional indicators as independent risk factors (31, 43). And ALB reduction has been independently shown to be closely related to precachexia/cachexia body composition, which indicated a worse prognosis and higher mortality (44–46). The results of our study were therefore consistent with previous research conclusions.

This study has several advantages. Firstly, most of the current studies only focus on partial inflammation markers, in our study, we had conducted a systematic and comprehensive analysis of all markers which have been proven to have predictive value in various studies, and screened out the factors combined with the highest predictive power to help clinical decision-making. Secondly, for the risk stratification of patients with recurrence, You R and his colleague established a special stratification system for operable patients (9). For inoperable patients, chemotherapy-based comprehensive treatment is the main treatment option but is short of specialized stratification systems. To the best of our knowledge, this study collected the largest number of patients who have been treated with chemotherapy-based comprehensive treatment after recurrence. Additionally, the markers selected in this study can be obtained from routine clinical examinations, which do not increase the economic burden on patients. At the same time, these markers have high accessibility and universality, and can be routinely available in any hospital.

Besides these strengths, this study has some limitations: firstly, as a retrospective study, we could not collect all information, such as Epstein-Barr Virus DNA or C-reactive protein (47, 48), whether there is a better factor combination in predicting OS remains to be ascertained. Secondly, all the data came from our institution, so sample bias may exist. However, it should not influence the results, as the cohort consisted of large sample size and all eligible patients were consecutively enrolled.

In conclusion, we established a prognostic stratification model for lrNPC patients who received chemotherapy-based comprehensive treatment, and we hope that our work can help clinicians develop individualized and accurate treatment strategies.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by Institutional Review Board of Sun Yat-sen University Cancer Center. Written informed consent for participation was not required for this study in accordance with the national legislation and the institutional requirements.

Study concept: YW,YT,Y-FX. Data acquisition: All authors. Statistical analysis and writing of manuscript: YW, YW. Supervision: Y-FX, YT. Manuscript review: All authors. All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

The study was supported by the Guangdong Hong-Kong Technology Cooperation Funding Science (No. 2021A0505110010), National Natural Science Foundation of China (No. 82103437), and Chinese Postdoctoral Science Foundation (No. 2021M693649).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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