Skip to main content

Joint modeling of longitudinal health-related quality of life during concurrent chemoradiotherapy period and long-term survival among patients with advanced nasopharyngeal carcinoma

Abstract

Background

To investigate the prognosis of longitudinal health-related quality of life (HRQOL) during concurrent chemoradiotherapy (CCRT) on survival outcomes in patients with advanced nasopharyngeal carcinoma (NPC).

Methods

During 2012–2014, 145 adult NPC patients with stage II-IVb NPC were investigated weekly using the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORCT QLQ-C30) during their CCRT period. The effects of longitudinal trends of HRQOL on survival outcomes were estimated using joint modeling, and hazard ratios (HRs) with 95% confidence intervals (95% CIs) were reported as a 10-point increase in HRQOL scores.

Results

After a median follow-up of 83.4 months, the multivariable models showed significant associations of longitudinal increasing scores in fatigue and appetite loss during the CCRT period with distant metastasis-free survival: 10-point increases in scores of fatigue and appetite loss domains during CCRT period were significantly associated with 75% (HR: 1.75, 95% CI: 1.01, 3.02; p = 0.047) and 59% (HR: 1.59, 95% CI: 1.09, 2.59; p = 0.018) increase in the risk of distant metastasis, respectively. The prognostic effects of the longitudinal HRQOL trend on overall survival and progress-free survival were statistically non-significant.

Conclusion

Increases in fatigue and appetite loss of HRQOL during the CCRT period are significantly associated with high risks of distant metastasis in advanced NPC patients. Nutritional support and psychological intervention are warranted for NPC patients during the treatment period.

Background

Nasopharyngeal carcinoma (NPC) is endemic in Southeastern Asia, especially in China [1]. Different from other head and neck cancers, NPC is significantly associated with Epstein-Barr virus infection and its major pathological type is non-keratinizing. Most NPC patients present at locally advanced stage at their initial diagnosis due to the conceal tumor-related symptoms on anatomical structure. Radical radiotherapy, such as intensity modulated radiotherapy (IMRT), is the current recommended treatment for NPC patients, and IMRT combined with chemotherapy is the primary treatment modality for locally advanced NPC patients [2]. Along with the improvements in early diagnosis and multimodality therapy, the prognosis of NPC has been largely improved in recent decades. The 5-year overall survival (OS) is over 90% for early-stage NPC patients and around 68–90% for locally advanced NPC patients [3, 4]. However, the treatment-related late side effects and sequela considerably reduce NPC survivors’ health-related quality of life (HRQOL) [5]. Our previous study has proved a substantially deteriorated trend of HRQOL during the concurrent chemoradiotherapy (CCRT) period among advanced NPC patients [6].

Previous studies have reported positive associations between pretreatment HRQOL and survival outcomes among patients with advanced lung carcinoma, breast carcinoma, multiple myeloma, melanoma, esophageal carcinoma, and head and neck carcinoma [7,8,9,10,11,12,13,14]. A few of studies reported that scores of some domains/items of HRQOL could predict distant metastasis and tumor recurrence in NPC and other head and neck cancers [15, 16]. One limitation of these studies is that HRQOL was measured at one time point (i.e., pretreatment) without considering its dynamic fluctuation during and after treatment. The longitudinal trend rather than only one measure of HRQOL might provide a more accuracy prediction of NPC prognosis. It has been reported that every 10-point increase of appetite loss during treatment and survival period resulted in a 13% increased risk of death in anaplastic oligodendrogliomas patients [17]. However, how the longitudinally deteriorated HRQOL could affect the long-term survival of NPC patients is still unclear. It is therefore necessary to investigate the effect of longitudinal HRQOL on long-term survival of NPC patients.

HRQOL is dynamically changing during the treatment and survival period of NPC patients, and often correlated with the length of survival period. Treatment and treatment-related impairment of HRQOL might affect survival. Separate analysis of longitudinal and survival data would lead to biased estimations [18]. Joint modeling, which brings both longitudinal measures and time-to-event outcomes together (simultaneously) into a single model, could provide unbiased estimations for longitudinal HRQOL, survival processes, and their association [18] [19]. Therefore, it could be a promising approach to better characterize the effect of longitudinal HRQOL on long-term survival outcomes [20]. Using the updated follow-up data from a multicenter clinical trial conducted in China, this study is objectively to investigate the impact of longitudinal HRQOL during treatment period on the long-term survival outcomes among advanced NPC patients using joint modeling approach.

Methods

Study design and participants

This study was based on an open-label, noninferiority, multicenter randomized clinical trial during 2012–2014 in China [21]. In the trial, patients, who were aged 18–65 years with non-keratinizing clinical stage of II-IVB (T1–4N1–3 or T3–4N0) NPC, no evidence of distant metastasis, a Karnofsky score ≥ 70, and adequate hematological, renal, hepatic functions, were randomly allocated (1:1) to cisplatin-based or nedaplatin-based concurrent chemoradiotherapy groups. The exclusion criteria include prior or synchronous malignant disease, primary relapse/distant metastasis, previously received radiotherapy or chemotherapy, pregnancy and lactating mothers, the presence of uncontrolled life-threatening illness, or with any mental disorder or somatic comorbidities of clinical concerns. In this study, a subsample of 145 patients who completed European Organization for Research and Treatment of Cancer Quality of Life Questionnaire core 30 (EORCT QLQ-C30) at baseline were involved, and their survival outcomes were updated from 31 June 2017 to 31 December 2020. Details of participants in this study has been reported previously [6].

Measures of health-related quality of life

HRQOL was measured at baseline (i.e., before treatment initiation) and repeatedly evaluated weekly to week 6 (around the end of CCRT) during the CCRT period, using the Chinese version of the EORCT QLQ-C30 (version 3.0). The EORCT QLQ-C30 has been widely used in several international cancer clinical trials [22, 23]. All assessments were carried out by a well-trained clinical research coordinator at the clinic. The fifteen domains of HRQOL, including a global quality of life, five multi-item functioning scales (i.e., physical, role, emotional, cognitive, and social functioning), three multi-item symptom scales (fatigue, pain, and nausea/vomiting), and six single symptom items (dyspnea, insomnia, appetite loss, constipation, diarrhea, and financial difficulties), were measured by 30 items. All domain scores were normalized into the range from 0 to 100, with higher scores indicating a better global health status, better performance of functioning, or higher levels of symptoms.

Survival outcomes

This study focused on three survival outcomes, including OS, progression-free survival (PFS), and distant metastasis-free survival (DMFS). OS was defined as the time interval from the date of random assignment to the date of death from any cause or censored at the date of last follow-up. PFS was defined as the time interval from the date of random assignment to the date of local or regional relapse, distant metastasis, or death from any cause, whichever occurred first. DMFS was defined as the time interval from the date of random assignment to the date of distant metastasis, or death from any cause.

Statistical analysis

Descriptive statistics (e.g., means and standard deviation (SD), frequency and percentage) were presented when appropriate. We firstly assessed the associations between baseline HRQOL domains and survival outcomes by cox regression models. Secondly, the associations between longitudinal assessments of HRQOL during the CCRT period and subsequently long-term survival outcomes were estimated using joint modeling method [18]. Joint modeling could simultaneously analyze the longitudinal data of the covariates and time-to-event data, which consists of a longitudinal component to model longitudinal trend of HRQOL and a survival component to model time-to-event outcomes. A linear mixed-effect model that expands the time effect into a B-spline basis matrix was used for longitudinal trend of HRQOL, and an exponential hazard model was used for time-to-event outcomes. The longitudinal and survival components were jointed through a random slope effect as shared parameter with a time lag of 12 months, to associate the true levels of longitudinal trend of HRQOL domains with the risk of a survival outcome (i.e., OS, PFS, or DMFS) [24]. The hazard ratios (HRs) with 95% confidence intervals (95% CIs) were reported as the 10-point increase of HRQOL domain scores, which is the minimal clinically important difference of the scales [25]. The SAS macro JM was applied for the joint modeling analyses [26].

All models were adjusted for age, sex, percentage of weight loss during CCRT period, AJCC stage, EBV-DNA copies before treatment, and treatment group. All data analyses were performed using SAS software (version 9.4, SAS Institute, Cary, NC, USA), and a two-sided p value < 0.05 was considered as statistically significant.

Ethical approval

This study was approved by the institutional review board of Sun Yat-sen University Cancer center. The authenticity of this article has been validated by uploading the key raw data onto the Research Data Deposit (www.researchdata.org.cn), with the approval RDD number as RDDA2022748620.

Results

Patients’ characteristics

Among 145 patients, the mean age was 44.7 years (SD: 9.3) in the cisplatin group and 43.8 years (SD: 10.3) in the nedaplatin group. Most patients were female, 74.7% in the cisplatin group and 74.3% in the nedaplatin group, 30.7% in cisplatin group and 27.1% in nedaplatin group reported more than 10% of weight loss during CCRT period. (Table 1).

Table 1 Descriptions of sample characteristics

Updated long-term survival rate

After a median follow-up of 83.4 months (range: 5.0, 100.7 months), 20 dead cases, 30 progressed cases, and 16 distant metastasis cases were observed. The 5-year and 8-year overall survival rates were 90.8% (95% CI: 84.7, 94.5) and 82.9% (95% CI: 73.2, 89.3), respectively. The 5-year and 8-year PFS rates were 82.5% (95% CI: 75.2, 87.8) and 75.9% (95% CI: 66.0, 83.3), while the 5-year and 8-year DMFS rates were 90.2% (95% CI: 84.0, 94.1), and 88.5% (95% CI: 81.9, 92.8), respectively. (Fig. 1).

Fig. 1
figure 1

Kaplan–Meier survival curve of progression-free survival (PFS), distant metastasis-free survival (DMFS), and overall survival (OS)

Joint modeling of longitudinal scores of HRQOL with survival outcomes

After adjustment of potential covariates, the results in Table 2 showed significant effects of longitudinal trend in fatigue and appetite loss during CCRT period on DMFS: a 10-point increase in scores of fatigue and appetite loss domains over time was associated with 75% (HR: 1.75, 95%CI: 1.01, 3.02; p = 0.047) and 59% (HR: 1.59, 95%CI: 1.09, 2.59; p = 0.018) increase in the risk of distant metastasis, respectively. The associations of other domains of HRQOL with DMFS were not statistically significant. The scores of HRQOL domains, neither at baseline nor longitudinal trend, showed statistical significance with OS and PFS (Table S1 and Table S2).

Table 2 Associations between health-related quality of life and distant metastasis-free survival among advance nasopharyngeal carcinoma

Discussion

To the best of our knowledge, this is the first study to investigate the prognostic effects of longitudinal HRQOL on the long-term survival outcomes in advanced NPC patients, showing that the deteriorated trends of fatigue and appetite loss during CCRT period were significantly associated with lower rates of DMFS.

Fatigue is one of the most prevalent cancer-related symptoms, especially for locally advanced NPC patients [6, 27], and few studies explored its associations with long-term survival in cancer patients. Antolín et al. reported that intensity of fatigue was associated with decreased quality of life but not with metastasis status among prostate cancer [28]. One possible mechanisms of our findings could be the inflammatory changes. Fatigue was found to be significantly associated with the increases of inflammation markers (e.g., IL6, sTNFR2) in head and neck cancer patients during treatment [29].These inflammatory changes could suppress the immune system [30, 31], and increase the risk of distant metastasis. Another possible mechanism might be hyponatremia. Fatigue is associated with hyponatremia, which was reported to be linked with lower survival rate in patients with lung cancer [32, 33], epithelial ovarian cancer [34], gastric cancer [35], and colorectal cancer [36]. Besides, Workeneh et al. indicated that hyponatremia can reduce the likelihood of survival [37], it is therefore necessary to take care of hyponatremia during anti-cancer treatment.

We also found that longitudinal trend of appetite loss during treatment period was significantly associated with lower DMFS in advanced NPC patients, which highlighted the importance of appetite and nutritional support for advanced NPC patients during treatment period. One possible reason could be that appetite loss could directly reduce patients’ nutrition intake and could cause clinically significant weight loss [38, 39], which was associated with a lower rate of DMFS among head and neck patients [40, 41]. Such weight loss, or even malnutrition, could downregulate the immune system, which might lead to unidentified micro-metastasis of metastatic cancer cells. Specifically, tumor immune escape and the initiation of metastasis are critical steps in the malignant progression of tumors [42]. Recruitment of immunosuppressive cells to tumors could protect metastatic cancer cells from surveillance by killer cells, which nullifies the effects of immunotherapy and thus establishes metastasis [43].

The main advantage of our study is that the dynamic effects of longitudinal measures of HRQOL on survival outcomes were estimated by joint modeling, which should have less bias than using only one single measure of HRQOL without considering its dynamic changes. However, there are several limitations in our study. First, the sample is small, especially for limited events of disease progress, distant metastasis, and death. Future studies with large sample size are warranted to confirm our findings. Second, HRQOL in our study was only weekly measured during treatment period, which could not reflect their long-term dynamic profiles after the treatment, and the impact of their dynamic changes during long-term survival period on prognosis of NPC patients is still unclear, and warranted in further research. Third, the generalizability of our finding might be limited by the representativeness of the sample, considering that patients only from one cancer center of epidemic region.

In conclusion, our findings indicate that the longitudinal deteriorated trends in fatigue and appetite loss during treatment period were significantly associated with higher risks of distant metastasis among advanced NPC patients. Proper psychological supportive care nutritional support during treatment period could potentially benefit treatment effects and long-term prognosis of NPC patients.

Availability of data and materials

The authenticity of this article has been validated by uploading the key raw data onto the Research Data Deposit (www.researchdata.org.cn), with the approval RDD number as RDDA2022748620.

References

  1. Sung H, Ferlay J, Siegel RL. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49.

    Article  PubMed  Google Scholar 

  2. Bossi P, Chan AT, Licitra L, Trama A, Orlandi E, Hui EP, Halámková J, Mattheis S, Baujat B, Hardillo J, et al. Nasopharyngeal carcinoma: ESMO-EURACAN clinical practice guidelines for diagnosis, treatment and follow-up(†). Ann Oncol Off J Eur Soc Med Oncol. 2021;32(4):452–65.

    Article  CAS  Google Scholar 

  3. Chen YP, Chan ATC, Le QT, Blanchard P, Sun Y, Ma J. Nasopharyngeal carcinoma. Lancet (London, England). 2019;394(10192):64–80.

    Article  PubMed  Google Scholar 

  4. Zhi-Qiang W, Qi M, Ji-Bin L, Rui Y, You-Ping L, Rui S, Guang-Yuan H, Ming-Yuan C, Yi-Jun H. The long-term survival of patients with III-IVb stage nasopharyngeal carcinoma treated with IMRT with or without Nimotuzumab: a propensity score-matched analysis. BMC Cancer. 2019;19(1):1122.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Bian X, Song T, Wu S. Outcomes of xerostomia-related quality of life for nasopharyngeal carcinoma treated by IMRT: based on the EORTC QLQ-C30 and H&N35 questionnaires. Expert Rev Anticancer Ther. 2015;15(1):109–19.

    Article  CAS  PubMed  Google Scholar 

  6. Li JB, Guo SS, Tang LQ, Guo L, Mo HY, Chen QY, Mai HQ. Longitudinal trend of health-related quality of life during concurrent chemoradiotherapy and survival in patients with stage II-IVb nasopharyngeal carcinoma. Front Oncol. 2020;10: 579292.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Dancey J, Zee B, Osoba D, Whitehead M, Lu F, Kaizer L, Latreille J, Pater JL. Quality of life scores: an independent prognostic variable in a general population of cancer patients receiving chemotherapy. The National Cancer Institute of Canada Clinical Trials Group. Qual Life Res Int J Qual Life Aspects Treatment Care Rehabil. 1997;6(2):151–8.

    CAS  Google Scholar 

  8. Ringdal GI, Götestam KG, Kaasa S, Kvinnsland S, Ringdal K. Prognostic factors and survival in a heterogeneous sample of cancer patients. Br J Cancer. 1996;73(12):1594–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Menon N, Patil V, Noronha V, Joshi A, Bhattacharjee A, Satam BJ, Mathrudev V, Ghosh Laskar S, Prabhash K. Quality of life in patients with locally advanced head and neck cancer treated with concurrent chemoradiation with cisplatin and nimotuzumab versus cisplatin alone - Additional data from a phase 3 trial. Oral Oncol. 2021;122: 105517.

    Article  CAS  PubMed  Google Scholar 

  10. Coates A, Porzsolt F, Osoba D. Quality of life in oncology practice: prognostic value of EORTC QLQ-C30 scores in patients with advanced malignancy. Eur J Cancer. 1997;33(7):1025–30.

    Article  CAS  PubMed  Google Scholar 

  11. Langendijk H, Aaronson NK, de Jong JM, ten Velde GP, Muller MJ, Wouters M. The prognostic impact of quality of life assessed with the EORTC QLQ-C30 in inoperable non-small cell lung carcinoma treated with radiotherapy. Radiother Oncol J Eur Soc Ther Radiol Oncol. 2000;55(1):19–25.

    Article  CAS  Google Scholar 

  12. Wisløff F, Hjorth M. Health-related quality of life assessed before and during chemotherapy predicts for survival in multiple myeloma. Nordic Myeloma Study Group. Br J Haematol. 1997;97(1):29–37.

    Article  PubMed  Google Scholar 

  13. Blazeby JM, Brookes ST, Alderson D. The prognostic value of quality of life scores during treatment for oesophageal cancer. Gut. 2001;49(2):227–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  14. Kramer JA, Curran D, Piccart M, de Haes JC, Bruning P, Klijn J, Van Hoorebeeck I, Paridaens R. Identification and interpretation of clinical and quality of life prognostic factors for survival and response to treatment in first-line chemotherapy in advanced breast cancer. Eur J Cancer. 2000;36(12):1498–506.

    Article  CAS  PubMed  Google Scholar 

  15. Guo SS, Hu W, Chen QY, Li JM, Zhu SH, He Y, Li JW, Xia L, Ji L, Lin CY, et al. Pretreatment quality of life as a predictor of survival for patients with nasopharyngeal carcinoma treated with IMRT. BMC Cancer. 2018;18(1):114.

    Article  PubMed  PubMed Central  Google Scholar 

  16. van Nieuwenhuizen AJ, Buffart LM, Langendijk JA, Vergeer MR, Voortman J, Leemans CR, Verdonck-de Leeuw IM. Health-related quality of life and overall survival: a prospective study in patients with head and neck cancer treated with radiotherapy. Qual Life Res. 2021;30(4):1145–53.

    Article  PubMed  Google Scholar 

  17. Ediebah DE, Galindo-Garre F, Uitdehaag BM, Ringash J, Reijneveld JC, Dirven L, Zikos E, Coens C, van den Bent MJ, Bottomley A, et al. Joint modeling of longitudinal health-related quality of life data and survival. Qual Life Res. 2015;24(4):795–804.

    Article  PubMed  Google Scholar 

  18. Ibrahim JG, Chu H, Chen LM. Basic concepts and methods for joint models of longitudinal and survival data. J Clin Oncol. 2010;28(16):2796–801.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Desmée S, Mentré F, Veyrat-Follet C, Guedj J. Nonlinear mixed-effect models for prostate-specific antigen kinetics and link with survival in the context of metastatic prostate cancer: a comparison by simulation of two-stage and joint approaches. AAPS J. 2015;17(3):691–9.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Asar Ö, Ritchie J, Kalra PA, Diggle PJ. Joint modelling of repeated measurement and time-to-event data: an introductory tutorial. Int J Epidemiol. 2015;44(1):334–44.

    Article  PubMed  Google Scholar 

  21. Tang LQ, Chen DP, Guo L, Mo HY, Huang Y, Guo SS, Qi B, Tang QN, Wang P, Li XY, et al. Concurrent chemoradiotherapy with nedaplatin versus cisplatin in stage II-IVB nasopharyngeal carcinoma: an open-label, non-inferiority, randomised phase 3 trial. Lancet Oncol. 2018;19(4):461–73.

    Article  CAS  PubMed  Google Scholar 

  22. Vanbutsele G, Van Belle S, Surmont V, De Laat M, Colman R, Eecloo K, Naert E, De Man M, Geboes K, Deliens L, et al. The effect of early and systematic integration of palliative care in oncology on quality of life and health care use near the end of life: a randomised controlled trial. Eur J Cancer. 2020;124:186–93.

    Article  PubMed  Google Scholar 

  23. Klinkhammer-Schalke M, Steinger B, Koller M, Zeman F, Fürst A, Gumpp J, Obermaier R, Piso P, Lindberg-Scharf P. Diagnosing deficits in quality of life and providing tailored therapeutic options: Results of a randomised trial in 220 patients with colorectal cancer. Eur J Cancer. 2020;130:102–13.

    Article  PubMed  Google Scholar 

  24. Chesnaye NC, Tripepi G, Dekker FW, Zoccali C, Zwinderman AH, Jager KJ. An introduction to joint models-applications in nephrology. Clin Kidney J. 2020;13(2):143–9.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Osoba D, Rodrigues G, Myles J, Zee B, Pater J. Interpreting the significance of changes in health-related quality-of-life scores. J Clin Oncol. 1998;16(1):139–44.

    Article  CAS  PubMed  Google Scholar 

  26. Garcia-Hernandez A, Rizopoulos D. JM: a SAS macro to fit jointly generalized mixed models for longitudinal data and time-to-event responses. J Stat Softw. 2018;84(12):1–29.

    Article  Google Scholar 

  27. Chen LM, Yang QL, Duan YY, Huan XZ, He Y, Wang C, Fan YY, Cai YC, Li JM, Chen LP, et al. Multidimensional fatigue in patients with nasopharyngeal carcinoma receiving concurrent chemoradiotherapy: incidence, severity, and risk factors. Support Care Cancer. 2021;29(9):5009–19.

    Article  PubMed  Google Scholar 

  28. Rodríguez Antolín A, Martínez-Piñeiro L, Jiménez Romero ME, García Ramos JB, López Bellido D, Muñoz Del Toro J, García García-Porrero A, Gómez Veiga F. Prevalence of fatigue and impact on quality of life in castration-resistant prostate cancer patients: the vital study. BMC Urol. 2019;19(1):92.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Xiao C, Eldridge RC, Beitler JJ, Higgins KA, Chico CE, Felger JC, Wommack EC, Knobf T, Saba NF, Shin DM, et al. Association among glucocorticoid receptor sensitivity, fatigue, and inflammation in patients with head and neck cancer. Psychosom Med. 2020;82(5):508–16.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Weber D, O’Brien K. Cancer and cancer-related fatigue and the interrelationships with depression, stress, and inflammation. J Evidence-based Complement Alternat Med. 2017;22(3):502–12.

    Article  Google Scholar 

  31. Klimas NG, Broderick G, Fletcher MA. Biomarkers for chronic fatigue. Brain Behav Immun. 2012;26(8):1202–10.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Sandfeld-Paulsen B, Aggerholm-Pedersen N, Winther-Larsen A. Hyponatremia in lung cancer: Incidence and prognostic value in a Danish population-based cohort study. Lung cancer (Amsterdam, Netherlands). 2021;153:42–8.

    Article  CAS  PubMed  Google Scholar 

  33. Tiseo M, Buti S, Boni L, Mattioni R, Ardizzoni A. Prognostic role of hyponatremia in 564 small cell lung cancer patients treated with topotecan. Lung cancer (Amsterdam, Netherlands). 2014;86(1):91–5.

    Article  PubMed  Google Scholar 

  34. Hefler-Frischmuth K, Grimm C, Gensthaler L, Reiser E, Schwameis R, Hefler LA. Prognostic value of preoperative hyponatremia and thrombocytosis in patients with epithelial ovarian cancer. Wien Klin Wochenschr. 2018;130(19–20):575–80.

    Article  PubMed  Google Scholar 

  35. Xu J, Chen X, Wang X, Zhu C, Hu Y, Yang X, Xu C, Shen X. Preoperative hyponatremia and hypocalcemia predict poor prognosis in elderly gastric cancer patients. Cancer Manag Res. 2019;11:8765–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Castillo JJ, Glezerman IG, Boklage SH, Chiodo J 3rd, Tidwell BA, Lamerato LE, Schulman KL. The occurrence of hyponatremia and its importance as a prognostic factor in a cross-section of cancer patients. BMC Cancer. 2016;16:564.

    Article  PubMed  PubMed Central  Google Scholar 

  37. Workeneh BT, Jhaveri KD, Rondon-Berrios H. Hyponatremia in the cancer patient. Kidney Int. 2020;98(4):870–82.

    Article  CAS  PubMed  Google Scholar 

  38. Chapman KM, Nelson RA. Loss of appetite: managing unwanted weight loss in the older patient. Geriatrics. 1994;49(3):54–9.

    CAS  PubMed  Google Scholar 

  39. Behl D, Jatoi A. Pharmacological options for advanced cancer patients with loss of appetite and weight. Expert Opin Pharmacother. 2007;8(8):1085–90.

    Article  CAS  PubMed  Google Scholar 

  40. Du XJ, Tang LL, Mao YP, Guo R, Sun Y, Lin AH, Ma J. Value of the prognostic nutritional index and weight loss in predicting metastasis and long-term mortality in nasopharyngeal carcinoma. J Transl Med. 2015;13:364.

    Article  PubMed  PubMed Central  Google Scholar 

  41. Ghadjar P, Hayoz S, Zimmermann F, Bodis S, Kaul D, Badakhshi H, Bernier J, Studer G, Plasswilm L, Budach V, et al. Impact of weight loss on survival after chemoradiation for locally advanced head and neck cancer: secondary results of a randomized phase III trial (SAKK 10/94). Radiat Oncol (London, England). 2015;10:21.

    Article  Google Scholar 

  42. Liu Y, Cao X. Immunosuppressive cells in tumor immune escape and metastasis. J Mol Med (Berl). 2016;94(5):509–22.

    Article  PubMed  Google Scholar 

  43. Kitamura T, Qian BZ, Pollard JW. Immune cell promotion of metastasis. Nat Rev Immunol. 2015;15(2):73–86.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We greatly appreciated all participants and their families, as well as the medical, nursing, and research staff at the study centers.

Funding

This study was partly supported by grants from the National Natural Science Foundation of China (No.81803105, No.81425018, No.81672868, No.82002852 and No.81802775), National Key Research and Development Program of China (2022YFC2705005), Natural Science Foundation of Guangdong Province (No. 2018A030310238, No.2017A030312003), Medical Science and Technology Research Fund of Guangdong Province (No. A2018201), the Sun Yat-sen University Clinical Research 5010 Program, the Fundamental Research Funds for the Central Universities of Sun Yat-sen University (No. 22qntd4001), and China Medical Board, USA (No. 22–484).

Author information

Authors and Affiliations

Authors

Contributions

QY Chen, JB Li, and SS Guo conceived and designed the study; JB Li, SS Guo, T Liu, and LQ Tang acquired the data; JB Li, and ZC Lin conducted the statistical analyses; JB Li, and SS Guo drafted the manuscript. All authors contributed to the interpretation of the results and critical revision of the manuscript for important intellectual content, and approved the final version of the manuscript.

Corresponding author

Correspondence to Qiu-Yan Chen.

Ethics declarations

Ethics approval and consent to participate

This study was approved by the institutional review board of Sun Yat-sen University Cancer center and all the participates approved the inform consent.

Consent for publication

All the authors approved the consent for publication.

Competing interests

All authors declare no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Li, JB., Guo, SS., Liu, T. et al. Joint modeling of longitudinal health-related quality of life during concurrent chemoradiotherapy period and long-term survival among patients with advanced nasopharyngeal carcinoma. Radiat Oncol 19, 125 (2024). https://doi.org/10.1186/s13014-024-02473-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13014-024-02473-y

Keywords