Development and external validation of nomograms to predict the risk of skeletal metastasis at the time of diagnosis and skeletal metastasis-free survival in nasopharyngeal carcinoma

Nasopharyngeal carcinoma (NPC) is a malignant head and neck cancer with a distinct ethnic and geographic pattern of distribution; the highest incidences of NPC (30–80 cases per 10,000/year) are observed in southern China and South East Asia [ 1]. Developments in advanced imaging modalities and instrumentation have enabled more precise tumor staging. Currently, approximately 5–8% of cases of NPC have distant metastasis (M1) at first diagnosis; the skeleton is the most common distant metastasis site, representing 70% to 80% cases of M1 disease [ 2– 4]. Distant metastasis at diagnosis is associated with poorer survival outcomes and reduced quality of life. Moreover, research on M1 disease is sparse due to the poor survival outcomes of patients with skeletal metastases. However, increasing evidence indicates long-term survival and even a complete response can be achieved among a small proportion of patients with skeletal metastases, especially those who receive aggressive treatment [ 5]. This indicates different treatment methods could significantly improve the prognosis of selected high-risk M1 cases. However, solely relying on the TNM classification to predict the outcomes of patients with skeletal metastasis may result in inaccurate assessment, leading to unnecessary treatment and financial burdens or – even worse – the patient receiving a suboptimal treatment strategy. Moreover, individualized follow-up and treatment strategies may be required for specific subgroups of patients with different risks of skeletal metastasis.

Bone scintigraphy (BS) remains is the leading diagnostic method for bone metastasis during initial work-up as it is widely available and low cost. However, BS is not routinely conducted during follow-up as it has a low diagnostic sensitivity, especially for early bone metastatic lesions; metastases mainly located in the bone marrow are frequently not detected by BS [ 6]. Although 18F–FDG PET/CT has a higher sensitivity than BS for detecting bone metastases in primary NPC, 18F–FDG PET/CT technique is expensive [ 7]. However, differentiation of malignant and benign lesions on BS and 18F–FDG PET remains problematic, even for experienced nuclear physicians.

As far as we are aware, research on the frequency of bone metastases at initial diagnosis (SMAD) and skeletal metastasis-free survival (SMFS) in NPC is rare and narrowly-focused [ 8– 11]. The lack of such data hampers accurate patient staging and risk stratification and delays the design of more reliable treatment protocols, as the M1 category is a “catch-all” classification that includes patients whose treatment response could be potentially curable or incurable. Identifying subgroups of patients with different risks of bone metastasis could help determine the appropriate imaging techniques and follow-up timing in a more personalized manner. Furthermore, more accurate prediction of the risk of skeletal metastasis could provide valuable decision-making information for clinicians and patients.

Nomograms incorporate a variety of important factors and have been demonstrated to be reliable prediction tools for quantifying individual risk in cancer. Nomograms can provide more precise prognoses than the traditional TNM staging system in several tumor types. To date, there has been no attempt to establish nomograms to predict SMAD and SMFS in NPC. We hypothesized nomograms combining T category, N category and other objective laboratory indexes could generate more accurate predictive models for SMAD and SMFS. Therefore, we assessed the prognostic risk factors for SMAD and SMFS in a large cohort of patients with NPC and validated the resulting nomograms using an external cohort treated at two other institutions.

This is the first study to retrospectively assess a very large number of patients with NPC to evaluate the prognostic value of a wide range of clinical and laboratory parameters in order to establish effective prognostic tools for skeletal metastasis. The nomograms established in this analysis demonstrated superior discriminative ability compared to the TMM classification of the seventh edition of the UICC/AJCC staging system and enabled risk scoring for individual patients. The independent prognostic factors for skeletal metastasis (SMAD, SMFS) included N category, circulating EBV-DNA, LDH, ALP, HGB and CRP; each of these factors has been previously reported to play a vital role in tumor progression or metastasis.

Advanced N category was significantly associated with skeletal metastasis in this study, which reflects the assumption that the tumor cells responsible for distant metastasis disseminate from the lymph nodes, rather than the primary tumor. In agreement with our findings, high serum ALP has also previously been reported to be a negative prognostic factor for skeletal metastasis and is used in the clinic to predict the presence of bone metastases in a range of cancers, including lung cancer and prostate cancer [ 12, 13]. The hydrolase ALP dephosphorylates a variety of molecules. Serum ALP is usually low in healthy individuals, but increases during pregnancy and in patients with bile duct obstruction, kidney disease, hepatocellular carcinoma or bone metastasis [ 14– 18]. Yang et al. reported a high serum LDH level was an independent, unfavorable risk factor for overall survival (OS) and distant-metastasis free survival (DMFS) in non-metastatic NPC [ 19]. This study provides the first evidence that high serum LDH is an independent prognostic factor for skeletal metastasis in NPC. Rapid tumor cell proliferation initiates anaerobic glycolysis to produce energy, which requires the transformation of pyruvate to lactate by LDH, a key enzyme of glycolysis [ 20]. In addition, increased LDH levels lead to a low extracellular pH and activate the hypoxia-inducible factor (HIF) pathway, which is well-recognized to promote tumor growth, aggressiveness and distant metastasis [ 21– 25].

In the regions where NPC is endemic, EBV infection is associated with an increased risk of NPC, and plasma EBV DNA is a useful prognostic marker in both early and advanced NPC [ 26, 27]. The present study indicates that circulating EBV DNA is also an independent prognostic factor for skeletal metastasis in NPC. Leung et al. reported that the EBV DNA cutoff value of 4000 copies/mL could categorize patients with early-stage NPC into a high-risk subgroup (with similar survival outcomes to patients with stage III disease) and a low-risk subgroup (with similar survival outcomes to stage I disease) [ 28]. A previously-established nomogram for disease-free survival (DFS) revealed incorporation of plasma EBV DNA increased the C-index compared to the model that did not include EBV DNA [ 29]. In further confirmation of its prognostic value, plasma EBV DNA was incorporated as a significant factor into the prognostic models for SMAD and SMFS in this study, and resulted in more accurate risk discrimination for individual patients.

Reduced HGB was also an independent prognostic factor for poor SMAD, consistent with the report by Ong et al. [ 30]. Anemia is more common in patients with advanced stage disease and/or a poor performance status, both of which are associated with a higher probability of skeletal metastasis in NPC. Elevated CRP has been associated with advanced tumor classification, bone invasion and lymph node metastasis in NPC [ 31]. Similarly, CRP moderately enhanced the predictive ability of the SMFS nomogram in this study. The link between inflammation and cancer is well-recognized; prolonged exposure to proinflammatory cytokines may eventually result in the induction of CRP synthesis and is considered to be a prognostic factor in NPC [ 32, 33]. In the future, improving nutrition status, inflammatory status and immune function could potentially further improve the clinical outcome of patients with NPC.

The present study has several limitations. First, the time span of data collection was nearly 7 years for the data set. Therefore, the question of whether the nomograms can be applied to patients currently receiving treatment should be asked. However, at our institution, the pathologic examination has not changed during this period of time. Second, patient comorbidities were not assessed. Liu et al. previously reported that comorbidity could affect OS to some extent in NPC [ 34]. However, the diversity of comorbidities makes it difficult to establish categorized variables and quantify risk. Therefore, the prognostic significance of comorbidities should be assessed in future nomogram studies. Finally, whether this nomogram can be applied to younger patients (aged <18-years-old) or patients in areas with a low occurrence of NPC remains to be determined.

In summary, we have developed and externally-validated nomograms to predict SMAD and SMFS based on analyses of a relatively large number of patients with NPC. The nomograms provide significantly better discrimination than the current seventh TNM classification of the AJCC staging system and also enable individualized prognostication of skeletal metastasis. Moreover, the accuracy of the nomograms was validated using large datasets for patients treated at other two institutions. In conclusion, these nomograms represent useful tools for predicting skeletal metastasis, facilitating patient counseling, and providing timely surveillance and clinical assessments.

This is the first large cohort study to establish a prediction nomogram for skeletal metastasis in non-metastatic NPC; the predictive accuracy of the model was validated in an external cohort.