Rates of Serious Complications Estimated by the ACS-NSQIP Surgical Risk Calculator in Predicting Oncologic Outcomes of Patients Treated with Pancreaticoduodenectomy for Pancreatic Head Cancer

Risk stratification of postoperative pancreatic fistula and other complications following pancreatoduodenectomy. How far are we? A scoping review

PURPOSE

Pancreatoduodenectomy (PD) is a challenging procedure which is associated with high morbidity rates. This study was performed to make an overview of risk factors included in risk stratification methods both logistic regression models and models based on artificial intelligence algorithms to predict postoperative pancreatic fistula (POPF) and other complications following PD and to provide insight in the extent to which these tools were validated.

METHODS

Five databases were searched to identify relevant studies. Calculators, equations, nomograms, and artificial intelligence models that addressed POPF and other complications were included. Only PD resections were considered eligible. There was no exclusion of the minimally invasive techniques reporting PD resections. All other pancreatic resections were excluded.

RESULTS

90 studies were included. Thirty-five studies were related to POPF, thirty-five studies were related to other complications following PD and twenty studies were related to artificial intelligence predication models after PD. Among the identified risk factors, the most used factors for POPF risk stratification were the main pancreatic duct diameter (MPD) (80%) followed by pancreatic texture (51%), whereas for other complications the most used factors were age (34%) and ASA score (29.4%). Only 26% of the evaluated risk stratification tools for POPF and other complications were externally validated. This percentage was even lower for the risk models using artificial intelligence which was 20%.

CONCLUSION

The MPD was the most used factor when stratifying the risk of POPF followed by pancreatic texture. Age and ASA score were the most used factors for the stratification of other complications. Insight in clinically relevant risk factors could help surgeons in adapting their surgical strategy and shared decision-making. This study revealed that the focus of research still lies on developing new risk models rather than model validation, hampering clinical implementation of these tools for decision support.

The efficacy of the American College of Surgeons Surgical Risk Calculator in the prediction of postoperative complications in oncogeriatric patients after curative surgery for abdominal tumors

BACKGROUND

The American College of Surgeons (ACS) has developed a Surgical Risk Calculator (SRC) to predict postoperative surgical complications. No studies have reported the performance of the ACS-SRC in oncogeriatric patients. Our objective was to evaluate the predictive performance of the ACS-SRC in these patients, treated with curative surgery for an abdominal malignancy.

METHODS

This is a retrospective study including 136 patients who underwent elective abdominal oncological surgery, between 2017 and 2019, at our institution. Postoperative complications were classified according to the ACS-SRC, and its predictive performance was analyzed by assessing discrimination and calibration and using receiver operating characteristics and area under the curve (AUC).

RESULTS

Discrimination was adequate with AUC of 0.7113 (95% confidence interval [CI]: 1.062-1.202, p = 0.0001; Brier 0.198) for serious complications and 0.7230 (95% CI: 1.101-1.756, p = 0.0057; Brier 0.099) for pneumonia; and poor for sepsis, surgical site infection (SSI), and urinary tract infection (UTI) with AUCs of 0.6636 (95% CI: 1.016-1.353, p = 0.0299; Brier 0.142), 0.6167 (95% CI: 1.003-1.266, p = 0.0450; Brier 0.175), and 0.6598 (95% CI: 1.069-2.145, p = 0.0195; Brier 0.082), respectively.

CONCLUSION

The ACS-SRC is an adequate predictor for serious complications and pneumonia in oncogeriatric patients treated surgically for abdominal cancer. However, the predictive power of the calculator appears to be low for sepsis, UTI, and SSI.

Comparison of National Surgical Quality Improvement Program Surgical Risk Calculator, Trauma and Injury Severity Score, and American Society of Anesthesiologists Physical Status to predict operative trauma mortality in elderly patients

BACKGROUND

The Trauma and Injury Severity Score (TRISS) uses anatomical and physiologic variables to predict mortality. Elderly (65 years or older) trauma patients have increased mortality and morbidity for a given TRISS, in part because of functional status and comorbidities. These factors are incorporated into the American Society of Anesthesiologists Physical Status (ASA-PS) and National Surgical Quality Improvement Program Surgical Risk Calculator (NSQIP-SRC). We hypothesized scoring tools using comorbidities and functional status to be superior at predicting mortality, hospital length of stay (LOS), and complications in elderly trauma patients undergoing operation.

METHODS

Four level I trauma centers prospectively collected data on elderly trauma patients undergoing surgery within 24 hours of admission. Using logistic regression, five scoring models were compared: ASA-PS, NSQIP-SRC, TRISS, TRISS-ASA-PS, and TRISS-NSQIP-SRC.Brier scores and area under the receiver operator characteristics curve were calculated to compare mortality prediction. Adjusted R2 and root mean squared error were used to compare LOS and predictive ability for number of complications.

RESULTS

From 122 subjects, 9 (7.4%) died, and the average LOS was 12.9 days (range, 1-110 days). National Surgical Quality Improvement Program Surgical Risk Calculator was superior to ASA-PS and TRISS at predicting mortality (area under the receiver operator characteristics curve, 0.978 vs. 0.768 vs. 0.903; p = 0.007). Furthermore, NSQIP-SRC was more accurate predicting LOS (R2, 25.9% vs. 13.3% vs. 20.5%) and complications (R2, 34.0% vs. 22.6% vs. 29.4%) compared with TRISS and ASA-PS. Adding TRISS to NSQIP-SRC improved predictive ability compared with NSQIP-SRC alone for complications (R2, 35.5% vs. 34.0%; p = 0.046). However, adding ASA-PS or TRISS to NSQIP-SRC did not improve the predictive ability for mortality or LOS.

CONCLUSION

The NSQIP-SRC, which includes comorbidities and functional status, had superior ability to predict mortality, LOS, and complications compared with TRISS alone in elderly trauma patients undergoing surgery.

LEVEL OF EVIDENCE

Prognostic and Epidemiologic; Level III.

Development of a preoperative risk score on admission in surgical intermediate care unit in gastrointestinal cancer surgery

Background

Gastrointestinal cancer surgery continues to be a significant cause of postoperative complications and mortality in high-risk patients. It is crucial to identify these patients. Our study aimed to evaluate the accuracy of specific perioperative risk assessment tools to predict postoperative complications, identifying the most informative variables and combining them to test their prediction ability as a new score.

Methods

A prospective cohort study of digestive cancer surgical patients admitted to the surgical intermediate care unit of the Portuguese Oncology Institute of Porto, Portugal was conducted during the period January 2016 to April 2018. Demographic and medical information including sex, age, date from hospital admission, diagnosis, emergency or elective admission, and type of surgery, were collected. We analyzed and compared a set of measurements of surgical risk using the risk assessment instruments P-POSSUM Scoring, ACS NSQIP Surgical Risk Calculator, and ARISCAT Risk Score according to the outcomes classified by the Clavien-Dindo score. According to each risk score system, we studied the expected and observed post-operative complications. We performed a multivariable regression model retaining only the significant variables of these tools (age, gender, physiological P-Possum, and ACS NSQIP serious complication rate) and created a new score (MyIPOrisk-score). The predictive ability of each continuous score and the final panel obtained was evaluated using ROC curves and estimating the area under the curve (AUC).

Results

We studied 341 patients. Our results showed that the predictive accuracy and agreement of P-POSSUM Scoring, ACS NSQIP Surgical Risk Calculator, and ARISCAT Risk Score were limited. The MyIPOrisk-score, shows to have greater discrimination ability than the one obtained with the other risk tools when evaluated individually (AUC = 0.808; 95% CI: 0.755–0.862). The expected and observed complication rates were similar to the new risk tool as opposed to the other risk calculators.

Conclusions

The feasibility and usefulness of the MyIPOrisk-score have been demonstrated for the evaluation of patients undergoing digestive oncologic surgery. However, it requires further testing through a multicenter prospective study to validate the predictive accuracy of the proposed risk score.

Is the ACS-NSQIP Risk Calculator Accurate in Predicting Adverse Postoperative Outcomes in the Emergency Setting? An Italian Single-center Preliminary Study

Background

The ACS-NSQIP surgical risk calculator (SRC) is an open-access online tool that estimates the chance for adverse postoperative outcomes. The risk is estimated based on 21 patient-related variables and customized for specific surgical procedures. The purpose of this monocentric retrospective study is to validate its predictive value in an Italian emergency setting.

Methods

From January to December 2018, 317 patients underwent surgical procedures for acute cholecystitis (n = 103), appendicitis (n = 83), gastrointestinal perforation (n = 45), and intestinal obstruction (n = 86). Patients’ personal risk was obtained and divided by the average risk to calculate a personal risk ratio (RR). Areas under the ROC curves (AUC) and Brier score were measured to assess both the discrimination and calibration of the predictive model.

Results

The AUC was 0.772 (95%CI 0.722–0.817, p < 0.0001; Brier 0.161) for serious complications, 0.887 (95%CI 0.847–0.919, p < 0.0001; Brier 0.072) for death, and 0.887 (95%CI 0.847–0.919, p < 0.0001; Brier 0.106) for discharge to nursing or rehab facility. Pneumonia, cardiac complications, and surgical site infection presented an AUC of 0.794 (95%CI 0.746–0.838, p < 0.001; Brier 0.103), 0.836 (95%CI 0.790–0.875, p < 0.0001; Brier 0.081), and 0.729 (95%CI 0.676–0.777, p < 0.0001; Brier 0.131), respectively. A RR > 1.24, RR > 1.52, and RR > 2.63 predicted the onset of serious complications (sensitivity = 60.47%, specificity = 64.07%; NPV = 81%), death (sensitivity = 82.76%, specificity = 62.85%; NPV = 97%), and discharge to nursing or rehab facility (sensitivity = 80.00%, specificity = 69.12%; NPV = 95%), respectively.

Conclusions

The calculator appears to be accurate in predicting adverse postoperative outcomes in our emergency setting. A RR cutoff provides a much more practical method to forecast the onset of a specific type of complication in a single patient.

Oncologic impact of preoperative prognostic nutritional index change in resected pancreatic cancer following neoadjuvant chemotherapy

BACKGROUND

Although several studies have focused on the oncologic impact of the preoperative prognostic nutritional index (PNI), there is no study correlating the preoperative PNI changes with the oncologic outcome of resected pancreatic cancer following neoadjuvant chemotherapy (NAC).

METHODS

We retrospectively analyzed 107 pancreatic ductal adenocarcinoma patients who underwent NAC followed by surgical resection. ΔPNI was defined as post-NAC PNI subtracted from pre-NAC PNI. Patients were divided into high (≥-1.94, n = 54) and low ΔPNI groups (<-1.94, n = 53). Long-term oncologic outcomes, such as overall survival (OS) and disease-free survival (DFS), were compared. Univariate and multivariate analysis were used to identify independent prognostic factors.

RESULTS

The high ΔPNI group correlated with lower pre-NAC PNI (46.96 ± 4.68 vs. 51.77 ± 5.63, p < 0.001) and higher post-NAC PNI (50.05 ± 4.80 vs. 42.56 ± 7.44, p < 0.001) more than the low ΔPNI group. The high ΔPNI group was also associated with longer OS compared with the low ΔPNI group (mean OS: 63.97 months [95% CI: 49.95-77.99] vs. 41.16 months [95% CI: 27.66-54.66], p = 0.003); there was no significant difference in DFS (p > 0.05). Multivariate analysis revealed that low ΔPNI was an independent risk factor for OS (HR, 3.516; 95% CI, 1.885-6.558; p < 0.001), but not for DFS (p > 0.05).

CONCLUSIONS

Low ΔPNI (<-1.94) was an independent risk factor for the overall survival of resected pancreatic cancer patients following NAC. In the preoperative setting, improving the PNI can better the long-term oncologic outcome of this condition.

Impact of preoperative risk factors on outcome after gastrectomy

Background

Gastrectomy is associated with relevant postoperative morbidity. However, outcome of surgery can be improved by careful selection of patients. The objective of the current study was therefore to identify preoperative risk factors that might impact on patients’ further outcome after surgical resection.

Methods

Preoperative risk factors having respectively different surgical risk scores for major complex surgery (including Cologne Risk Score, p-/o-POSSUM, and NSQIP risk score) of patients that underwent gastrectomy for AEG II/III tumors and gastric cancer were correlated with complications according to Clavien-Dindo and outcome. Patients who underwent surgery in palliative intention were excluded from further analysis.

Results

Subtotal gastrectomy was performed in 23%, gastrectomy in 59%, and extended gastrectomy in 18% in a total of 139 patients (mean age: 64 years old). Thirty six percent experienced a minor complication (Dindo I-II) and 24% a major complication (Dindo III-V), which resulted in a prolonged hospital stay (p < 0.001). In-hospital mortality (=Dindo V) was 2.5%. Besides age, type of surgical procedure impacted on complications with extended gastrectomy showing the highest risk (p = 0.005). The o-POSSUM score failed to predict mortality accurately. We observed a highly positive correlation between predicted morbidity respectively mortality and occurrence of complications estimated by p-POSSUM (p = 0.005), Cologne Risk (p = 0.007), and NSQIP scores (p < 0.001).

Conclusion

The results demonstrate a significant association between different risk scores and occurrence of complications following gastrectomy. The p-POSSUM, Cologne Risk, and NSQIP score exhibited superior performance than the o-POSSUM score. Therefore, these scores might allow identification and selection of high-risk patients and thus might be highly useful for clinical decision making.