Defining the optimal threshold and prognostic utility of pre-treatment hemoglobin level as a biomarker for survival outcomes in head and neck cancer patients receiving chemoradiation

Development and external validation of a machine learning-based model to predict postoperative recurrence in patients with duodenal adenocarcinoma: a multicenter, retrospective cohort study

BACKGROUND

Duodenal adenocarcinoma (DA) has a high recurrence rate, making the prediction of recurrence after surgery critically important.

METHODS

Our objective is to develop a machine learning-based model to predict the postoperative recurrence of DA. We conducted a multicenter, retrospective cohort study in China. 1830 patients with DA who underwent radical surgery between 2012 and 2023 were included. Wrapper methods were used to select optimal predictors by ten machine learning learners. Subsequently, these ten learners were utilized for model development. The model's performance was validated using three separate cohorts, and assessed by the concordance index (C-index), time-dependent calibration curve, time-dependent receiver operating characteristic curves, and decision curve analysis.

RESULTS

After selecting predictors, ten feature subsets were identified. And ten feature subsets were combined with the ten machine learning learners in a permutation, resulting in the development of 100 predictive models, and the Penalized Regression + Accelerated Oblique Random Survival Forest model (PAM) exhibited the best predictive performance. The C-index for PAM was 0.882 (95% CI 0.860-0.886) in the training cohort, 0.747 (95% CI 0.683-0.798) in the validation cohort 1, 0.736 (95% CI 0.649-0.792) in the validation cohort 2, and 0.734 (95% CI 0.674-0.791) in the validation cohort 3. A publicly accessible web tool was developed for the PAM.

CONCLUSIONS

The PAM has the potential to identify postoperative recurrence in DA patients. This can assist clinicians in assessing the severity of the disease, facilitating patient follow-up, and aiding in the formulation of adjuvant treatment strategies.

The Importance of Hypoxia-Related to Hemoglobin Concentration in Breast Cancer

The importance of hemoglobin (Hgb) as a novel prognostic biomarker in predicting clinical features of cancers has been the subject of intense interest. Anemia is common in various types of cancer including breast cancer (BC) and is considered to be attributed to tumoral hypoxia. Cancer microenvironments are hypoxic compared with normal tissues, and this hypoxia is associated with Hgb concentration. Recent preclinical documents propose a direct or indirect correlation of intratumoral hypoxia, specifically along with acidity, with Hgb concentration and anemia. Analysis of the prognostic value of Hgb in BC patients has demonstrated increased hypoxia in the intratumoral environment. A great number of studies demonstrated that lower concentrations of Hgb before or during common cancer treatments, such as radiation and chemotherapy, is an essential risk factor for poor prognostic and survival, as well as low quality of life in BC patients. This data suggests a potential correlation between anemia and hypoxia in BC. While low Hgb levels are detrimental to BC invasion and survival, identification of a distinct and exact threshold for low Hgb concentration is challenging and inaccurate. The optimal thresholds for Hgb and partial pressure of oxygen (pO2) vary based on different factors including age, gender, therapeutic approaches, and tumor types. While necessitating further investigations, understanding the correlation of Hgb levels with tumoral hypoxia and oxygenation could improve exploring strategies to overcome radio-chemotherapy related anemia in BC patients. This review highlights the collective association of Hgb concentration and hypoxia condition in BC progression.

Peripheral hemoglobin to albumin ratio predicts prognosis in patients with nasopharyngeal carcinoma underwent concurrent chemoradiotherapy

BACKGROUND

Recently, the hemoglobin to albumin ratio (HAR) has been shown to be closely associated with the survival of certain malignancies. However, its prognostic value in nasopharyngeal carcinoma (NPC) remained to be elucidated. Herein, we aimed to explore the correlation between HAR and overall survival (OS) in NPC patients treated with concurrent chemoradiotherapy (CCRT).

METHODS

This retrospective study included a total of 858 patients with NPC receiving CCRT between January 2010 and December 2014 in Sun Yat-sen University Cancer Center. We randomly divided them into the training cohort (N = 602) and the validation cohort (N = 206). We performed univariate and multivariate Cox regression analyses to identify variables associated with OS, based on which, a predictive nomogram was constructed and assessed.

RESULTS

In both the training and validation cohorts, patients were classified into low- and high-HAR groups according to the cutoff value determined by the maximally selected rank statistics. This HAR cutoff value effectively divided patients into two distinct prognostic groups with significant differences. Multivariable Cox analysis revealed that higher T-stage, N-stage, and HAR values were significantly related to poorer prognosis in NPC patients and served as independent prognostic factors for NPC. Based on these, a predictive model was constructed and graphically presented as a nomogram, whose predictive performance is satisfactory with a C-index of 0.744 [95%CI: 0.679-0.809] and superior to traditional TNM staging system [C-index = 0.609, 95%CI: 0.448-0.770].

CONCLUSION

The HAR value was an independent predictor for NPC patients treated with CCRT, the predictive model based on HAR with superior predictive performance than traditional TNM staging system might improve individualized survival predictions.

Development and validation of nomogram models for predicting postoperative prognosis of early-stage laryngeal squamous cell carcinoma

BACKGROUND

We aimed to investigate the postoperative prognosis in patients with early-stage laryngeal squamous cell carcinoma (LSCC) in association with the preoperative blood markers and clinicopathological characteristics and to develop nomograms for individual risk prediction.

METHODS

The clinical data of 353 patients with confirmed early-stage LSCC between 2009 and 2018 were retrospectively retrieved from the First Affiliated Hospital with Nanjing Medical University. All patients were randomly divided into the training and testing groups in a 7:3 ratio. Univariate and multivariate analyses were performed, followed by the construction of nomograms to predict recurrence-free survival (RFS) and overall survival (OS). Finally, the nomograms were verified internally, and the predictive capability of the nomograms was evaluated and compared with that of tumour T staging.

RESULTS

Univariate and multivariate analyses identified platelet counts (PLT), fibrinogen (FIB), and platelet to lymphocyte ratio (PLR) were independent factors for RFS, and FIB, systemic immune-inflammation index (SII), and haemoglobin (HGB) were independent prognostic factors for OS. The nomograms showed higher predictive C-indexes than T staging. Furthermore, decision curve analysis (DCA) revealed that the net benefit of the nomograms' calculation model was superior to that of T staging.

CONCLUSIONS

We established and validated nomograms to predict postoperative 1-, 3- and 5-year RFS and OS in patients with early-stage LSCC based on significant blood markers and clinicopathological characteristics. These models might help clinicians make personalized treatment decisions.

Host-related indexes in head and neck cancer

PURPOSE OF REVIEW

Peripheral blood host-related indexes have been widely studied in cancer patients. Several authors have shown the prognostic capacity of these indexes in head and neck cancer. Therefore, there has been an increasing interest in this topic recently.

RECENT FINDINGS

The main variables analyzed and used to create these host-related indexes are peripheral blood leukocytes - including neutrophils, monocytes and lymphocytes - albumin and hemoglobin levels. Other factors with proven prognostic capacity in some studies are: platelets, C-reactive protein, and BMI. Among all the combined indexes, the neutrophil-to-lymphocyte ratio has been the most accepted and used worldwide. Nonetheless, there are other indexes which group multiple of these factors that have shown better prognostic capacity, and are promising in the near future.

SUMMARY

Host-related indexes are ideal biomarkers to be used on our daily-basis. There is enough evidence to start considering them when assessing patients with head and neck cancer.

p16 Overexpression in Sinonasal Squamous Cell Carcinoma: Association with Human Papillomavirus and Prediction of Survival Outcomes

p16 overexpression is often used as a surrogate marker for human papillomavirus (HPV) infection in oropharyngeal squamous cell carcinoma but remains an uncertain diagnostic tool for HPV-related sinonasal squamous cell carcinoma (SNSCC). Our study involved 79 consecutive SNSCC patients who were treated at a tertiary referral university hospital during 2006-2021. We retrospectively examined their clinical characteristics and conducted p16 immunohistochemistry and HPV detection. We found that 12.7% of the patients exhibited p16 overexpression, which was significantly more common in the nasal cavity and increased from 2015 onward. The HPV was a high-risk type and viral loads ranged from 4.2 to 1.6 × 106 copies/ng DNA with genome integration. Five-year overall survival (OS) and five-year relapse-free survival (RFS) rates were 74.6% and 69.9%, respectively. Our multivariate analysis showed that T category (T1-4a) and hemoglobin levels (≥13.7) were significant favorable prognostic factors for OS, while T category, performance status, and p16 overexpression were significantly associated with RFS. In patients with p16 overexpression, OS was 100% and RFS was 90%. Our findings suggest that p16 overexpression is a reliable surrogate marker for transcriptionally active HPV infection and predicts a favorable prognosis.

Analysis of prognostic factors and establishment of prognostic model for primary mediastinal germ cell tumors: a case controlled study

BACKGROUND

The overall prognosis of primary mediastinal germ cell tumors (PMGCTs) is poor and the associated prognostic factors are not fully understood. Our goal was to investigate the prognostic factors of PMGCTs and to develop a validated prognostic prediction model.

MATERIALS AND METHODS

A total of 114 PMGCTs with specific pathological types were included in this study. Clinicopathological characteristics of nonseminomatous PMGCTs and mediastinal seminomas were compared using the χ2 or Fisher's exact test. Independent prognostic factors of nonseminomatous PMGCTs screened using the univariate and multivariate Cox regression analysis were then used to generate a nomogram. The predictive performance of the nomogram was evaluated using the concordance index, decision curve, and the area under the receiver operating characteristic curve (AUC) and validated by bootstrap resampling. The Kaplan-Meier curves of independent prognostic factors were analyzed.

RESULTS

This study included 71 cases of nonseminomatous PMGCTs and 43 cases of mediastinal seminomas. The 3-year overall survival rates for nonseminomatous PMGCTs and mediastinal seminomas patients were 54.5 and 97.4%, respectively. The overall survival prognostic nomogram for nonseminomatous PMGCTs was established by integrating independent prognostic factors, including the Moran-Suster stage, white blood cell, hemoglobin, and platelet-lymphocyte ratio. The nomogram demonstrated good performance with a concordance index of 0.760 and the 1-year and 3-year AUC values of 0.821 and 0.833, respectively. These values were better than those of the Moran-Suster stage system. The bootstrap validation had an AUC of 0.820 (0.724-0.915) and showed a well-fitting calibration curve. Besides, patients with mediastinal seminomas showed favorable clinical outcomes and all the nine patients received neoadjuvant therapy and postoperative surgery achieved pathological complete response.

CONCLUSION

A nomogram based on staging and blood routine examination results was established to accurately and consistently predict the prognosis of patients with nonseminomatous PMGCTs.

Association of neutrophil-lymphocyte ratio with survival in peripheral early-stage non-small cell lung cancer after stereotactic body radiation therapy

BACKGROUND

The role of neutrophil-lymphocyte ratio (NLR) as a predictor for survival in single fraction SBRT-treated non-small cell lung cancer (NSCLC) patients remains unclear. We performed an observational cohort study to determine the role of pretreatment NLR in predicting survival of early-stage NSCLC patients after single fraction SBRT.

METHODS

A single-institution database of peripheral early-stage NSCLC patients treated with SBRT from February 2007 to May 2022 was queried. Optimal threshold of neutrophil-lymphocyte ratio (NLR) was defined based on maximally selected rank statistics. Cox multivariable analysis (MVA), Kaplan-Meier, and propensity score matching were performed to evaluate outcomes.

RESULTS

A total of 286 patients were included for analysis with median follow up of 19.7 months. On Cox multivariate analysis, as a continuous variable, NLR was shown to be an independent predictor of OS (adjusted hazards ratio [aHR] 1.06, 95% CI 1.02-1.10, p = 0.005) and PFS (aHR 1.05, 95% CI 1.01-1.09, p = 0.013). In addition, NLR was associated with DF (aHR 1.11, 95% CI 1.05-1.18, p < 0.001). Maximally selected rank statistics determined 3.28 as the cutoff point of high NLR versus low NLR. These findings were confirmed upon propensity matching.

CONCLUSIONS

Pretreatment NLR is an independent predictor for survival outcomes of peripheral early-stage NSCLC patients after single fraction SBRT.