Is Preoperative Serum Albumin Predictive of Adverse Outcomes in Head and Neck Cancer Surgery?

The Naples Prognostic Score Exerts a Significant Impact on the Prognosis of Patients Diagnosed with External Auditory Canal Carcinoma After Surgery

Background

External auditory canal carcinoma (EACC) is a rare malignant tumor. This study aimed to investigate the influence of the comprehensive index of nutrition- Naples prognostic score (NPS) on the prognosis of EACC patients with surgical resection.

Methods

A total of 73 EACC patients with surgical resection were selected from two tertiary medical institutions, and were diagnosed between Sep 2008 and Aug 2019. The univariate and multivariate Cox regression analyses were used to identify the independent prognostic factors for disease-free survival (DFS) and overall survival (OS) for postoperative EACC patients. The prognosis for postoperative EACC patients with varying NPS were displayed by Kaplan-Meier plots.

Results

The 3- and 5-year survival rate for EACC patients with surgical resection were 72.6%, 32.9% for DFS, and 76.7%, 52.1% for OS, respectively. The multivariate Cox regression analysis revealed that advanced Pittsburgh stage, perineural invasion, vascular invasion, and higher NPS were identified as independent prognostic factors for DFS. Additionally, advanced Pittsburgh stage, vascular invasion, an ACCI score of 6 or higher, and higher NPS were found to be independent predictors for OS.

Conclusion

NPS serves as a crucial predictor of postoperative outcomes in patients with EACC, with higher levels indicating poorer disease-free and overall survival. Additionally, factors such as Pittsburgh stage, perineural and vascular invasion, and ACCI are also significant prognostic indicators.

Geriatric Nutritional Risk Index and Postoperative Outcomes Following Head and Neck Cancer Surgery

BACKGROUND

The geriatric nutritional risk index (GNRI) is a tool to assess preoperative nutritional status that can be calculated simply based on height, weight, and serum albumin. This study assesses the utility of GNRI in predicting postoperative complications in patients undergoing major head and neck cancer (HNC) surgery.

METHODS

Retrospective review of the 2016-2020 National Surgical Quality Improvement Program database. Patients were categorized into GNRI > 98 (normal nutritional status), GNRI 92-98 (moderate malnutrition status), and GNRI < 92 (severe malnutrition status). Univariable and multivariable binary logistic regression analyses were performed.

RESULTS

Sixteen thousand seven hundred eight-nine patients undergoing HNC resection were included. On multivariable analysis, moderate and severe malnourishment based on GNRI remained significantly associated with any surgical complication, any medical complication, any complication, Clavien-Dindo grade IV complications, and 30-day mortality.

CONCLUSIONS

GNRI may have utility as a potentially modifiable preoperative prognostic factor that can be optimized to improve complications and mortality following HNC resection.

LEVEL OF EVIDENCE

Level 4.

Prognostic significance of preoperative Naples prognostic score for disease-free and overall survival in oral cavity squamous cell carcinoma post-surgery

BACKGROUND

Oral cavity squamous cell carcinoma (OCSCC) is a common malignancy with high morbidity and mortality. This research seeks to assess the correlation between Naples Prognostic Score (NPS) and survival outcomes in patients with OCSCC who are receiving surgical treatment, highlighting its potential as a prognostic tool for predicting patient outcomes.

METHODS

This retrospective study included 589 OCSCC patients from two large regional medical centers in central China, treated between February 2008 and September 2019. Inclusion criteria mandated confirmed OCSCC diagnosis, age ≥ 18 years, and radical surgery, while patients with distant metastasis, multiple tumors, or insufficient data were excluded. Data on 29 clinicopathological variables, including demographic details, tumor characteristics, and nutritional/inflammatory markers, were collected. The statistical approach included both univariate and multivariate Cox regression models to determine factors associated with disease-free survival (DFS) and overall survival (OS). Additionally, Kaplan-Meier survival analysis was employed to evaluate the effect of adjuvant radiotherapy on survival in various NPS subgroups.

RESULTS

Surgical margin status, ENE, NPS, age-adjusted Charlson comorbidity index (ACCI), and American Joint Committee on Cancer (AJCC) stage were identified as independent prognostic factors for DFS. Similarly, Eastern Cooperative Oncology Group Performance Status (ECOG PS), surgical margin status, extranodal extension (ENE), NPS, ACCI, and AJCC stage were found to be independent prognostic factors for OS. A higher NPS was associated with a poorer prognosis. In AJCC stage III-IVb patients with NPS 1-2, adjuvant radiotherapy significantly improved both DFS and OS. Likewise, in AJCC stage III-IVb patients with NPS 3-4, adjuvant radiotherapy was associated with better DFS and OS outcomes. However, no significant impact of adjuvant radiotherapy was observed in patients with AJCC stage I-II or in those with NPS 0, regardless of stage. This underscores the importance of NPS in stratifying patients for adjuvant therapy.

CONCLUSION

The Naples Prognostic Score is a beneficial prognostic indicator for survival in OCSCC patients. Its integration into clinical practice may assist in risk stratification and treatment decision-making, particularly for those undergoing adjuvant radiotherapy.

Artificial intelligence prediction model for readmission after DIEP flap breast reconstruction based on NSQIP data

BACKGROUND

Readmissions following deep inferior epigastric perforator (DIEP) flap breast reconstruction represent a significant healthcare burden, yet current risk prediction methods lack precision in identifying high-risk patients. We developed a machine learning model to predict 30-day readmission risk using a large national surgical quality database.

METHODS

This retrospective analysis examined 13,312 DIEP flap procedures from the American College of Surgeons National Surgical Quality Improvement Program database (2016-2022). A stacked machine learning model was developed incorporating patient demographics, comorbidities, operative characteristics, and laboratory values. Model performance was assessed using accuracy, precision, recall, and F1 score.

RESULTS

The overall readmission rate was 5.42% (723 patients). The stacked model achieved 88% accuracy and 79% recall for readmission prediction with an area under the receiver operating characteristic curve of 0.8921 (95% CI: 0.853-0.927) on the test set. Key predictors included days from operation until superficial incisional surgical site infection complications, operative time, body mass index, and preoperative albumin.

CONCLUSION

This stacked machine learning approach demonstrates strong predictive capability for post-DIEP flap readmissions, with high sensitivity for identifying at-risk patients. The model's performance suggests clinical utility in preoperative risk stratification and resource allocation. Implementation could enable targeted intervention strategies to potentially reduce readmission rates in high-risk populations.

Development of a predictive nomogram based on preoperative inflammation-nutrition-related markers for prognosis in locally advanced lip squamous cell carcinoma after surgical treatment

BACKGROUND

The prognostic role of preoperative inflammation-nutrition-related markers in locally advanced lip squamous cell carcinoma (LSCC) remains underexplored. This study aimed to assess the impact of various preoperative inflammation-nutrition-related markers on the prognosis of patients with locally advanced LSCC undergoing surgical treatment and to establish a corresponding predictive model.

METHODS

A retrospective analysis was performed on the clinical data of 169 patients with locally advanced LSCC who underwent surgical treatment. A total of 27 clinicopathological variables, including inflammation-nutrition-related markers, were collected. Univariate and multivariate Cox regression analyses were used to identify independent prognostic factors for disease-free survival (DFS) and overall survival (OS). The nomogram models were validated using receiver operating characteristic (ROC) curve analysis, calibration plots, and decision curve analysis (DCA). Risk stratification was performed based on the nomogram scores, and differences between risk subgroups were explored.

RESULTS

The extranodal extension (ENE), surgical safety margin, Glasgow prognostic score (GPS), Geriatric Nutritional Risk Index (GNRI), Controlling Nutrition score (CONUT), American Joint Committee on Cancer (AJCC) stage, and adjuvant radiotherapy were independent prognostic factors for DFS. In contrast, ENE, surgical safety margin, GNRI, CONUT, AJCC stage, and adjuvant radiotherapy were also independent prognostic factors for OS. The nomograms demonstrated better predictive performance than the AJCC staging system. Based on the nomogram model, patients were stratified into low-, medium-, and high-risk subgroups, which exhibited significant differences in survival outcomes.

CONCLUSION

GPS, GNRI, and CONUT are independent factors affecting the prognosis of patients with locally advanced LSCC undergoing radical surgery. By combining GPS, GNRI, and COUNT with other independent clinicopathological prognostic factors, a reliable nomogram model can be established to accurately predict patients' DFS and OS. This provides a powerful tool for individualized prognostic assessment, optimized risk stratification, and treatment decision-making.

Hypoalbuminemia and Postoperative Outcomes Following Major Salivary Gland Resection

Objective

Hypoalbuminemia (HA) is a proxy for malnutrition that has been associated with postoperative complications in several surgical subspecialties. This study investigates the association between pre-operative HA and complications following major salivary gland (MSG) resection.

Methods

Patients undergoing outpatient, elective MSG resection were extracted from the 2005 to 2020 National Surgical Quality Improvement Program database. Demographics and comorbidities were compared between HA (preoperative serum albumin < 3.5 g/dL) and non-HA cohorts. To determine associations between albumin status and postoperative complications, univariate and multivariable binary logistic regression analyses were performed.

Results

A total of 5774 patients undergoing MSG resection were included, of which 321 (5.6%) had preoperative HA. HA was associated with older age on univariate analysis (65.2 vs. 60.2 years, p < 0.001). Multivariable analysis found HA to be independently associated with any surgical complication (OR 2.03, 95% CI 1.09-3.56, p = 0.019) and length of stay (LOS) ≥ 90th percentile (OR 1.58, 95% CI 1.04-2.38, p = 0.032).

Conclusion

Preoperative HA may be a poor prognostic factor associated with an increased risk of surgical complications and prolonged LOS among patients undergoing MSG resection.

Level of Evidence

4.

Development of a Prognostic Nomogram Incorporating the Naples Prognostic Score for Postoperative Oral Squamous Cell Carcinoma Patients

Background

The Naples prognostic score (NPS) and its relation to the prognosis of oral squamous cell carcinoma (OSCC) have been inconclusive. This study aimed to investigate the correlation between NPS and the prognosis of postoperative OSCC patients. Additionally, the study sought to develop a new nomogram for predicting disease-free survival (DFS) and overall survival (OS).

Methods

The study included 576 OSCC patients who underwent surgical treatment at two hospitals between August 2008 and June 2018. Univariate and multivariate Cox regression analyses were conducted to identify independent prognostic factors. Subsequently, two nomograms were developed to predict DFS and OS based on these factors and underwent rigorous validation.

Results

The median DFS and OS were 31.5 months and 36.5 months, respectively. Significant differences in DFS and OS were observed among patients with different NPS scores. Adjuvant radiotherapy, age-adjusted Charlson comorbidity index (ACCI), extranodal extension (ENE), NPS, American Joint Committee on Cancer (AJCC) stage, surgical safety margin, eastern cooperative oncology group performance status (ECOG PS), and systemic inflammation score (SIS) were identified as independent predictors of DFS and OS. In the training cohort, the nomogram's concordance index (C-index) for predicting DFS and OS was 0.701 and 0.693, respectively. In the validation group, the corresponding values were 0.642 and 0.635, respectively. Calibration plots confirmed a high level of agreement between the model's predictions and actual outcomes. Decision curve analysis (DCA) demonstrated the nomogram's good clinical utility. Additionally, patients in the low-risk group did not benefit from adjuvant radiotherapy, while those in the medium-risk and high-risk group could benefit from adjuvant radiotherapy.

Conclusion

NPS significantly influences the prognosis of OSCC patients following surgery. The nomogram developed in this study holds significant clinical application potential. The low-risk subgroup of patients was not required to undergo postoperative radiotherapy.

A Low Systemic Inflammatory Response Index Is Associated With Improved Survival in Adenoid Cystic Carcinoma Patients

BACKGROUND

Predicting the long-term survival in adenoid cystic carcinoma (ACC) patients remains challenging. Inflammatory cell-based indices are emerging as prognostic indicators of oncology.

PURPOSE

This study aimed to determine the associations between the preoperative systemic inflammatory response index (SIRI) and the systemic immunoinflammatory index (SII) and the 10-year survival rates in patients with ACC of the head and neck (ACCHN).

STUDY DESIGN, SETTING, SAMPLE

This retrospective cohort study comprised ACCHN patients treated at the Chinese People's Liberation Army General Hospital between November 2003 and December 2020.

PREDICTOR VARIABLE

The inflammatory response, assessed using the SIRI and SII, was the predictor variable. The optimal cutoff values were based on the maximum Youden index values (sensitivity ＋ specificity－1). The patients were divided into two groups each, based on the SIRI (low, ≤ 0.15) and (high, > 0.15), and SII (low, ≤ 562.8 and high, > 562.8) values.

MAIN OUTCOME VARIABLE(S)

Overall survival (OS), or the number of days, weeks, or months between treatment initiation and death (or the last follow-up date), was the primary outcome variable.

COVARIATES

The covariates were classified as demographic (age, gender, body mass index), medical (hypertension, diabetes), inflammatory (neutrophils, lymphocytes, monocytes, platelets, lymphocyte-monocyte ratio, platelet-lymphocyte ratio, neutrophil-lymphocyte ratio), and perioperative (tumor stage, lymph node metastasis, tumor size, treatment type).

ANALYSES

Descriptive, univariate, and multivariate Cox proportional risk regression analyses were performed to determine whether the SIRI and SII were independent prognostic factors for OS. Kaplan-Meier survival curves and log-rank tests were used to determine their associations with the OS.

RESULTS

The study sample comprised 162 patients (mean age, 52 ± 14; males, 39.5%). The median follow-up time was 6.81 ± 0.23, and the 10-year OS rate was 7.68 ± 0.25. The low and high SIRI groups comprised 109 and 53 patients, while the low and high SII groups comprised 116 and 46 patients, respectively. SIRI was identified as a prognostic factor (P < .01; hazard ratio, 2.45; 95% confidence interval, 1.35-4.45).

CONCLUSION AND RELEVANCE

The SIRI has the advantages of reproducibility, convenience, noninvasiveness, and affordability, making it a promising prognostic inflammatory index for patients with ACCHN.