Red blood cell transfusions and the survival in patients with cancer undergoing curative surgery: a systematic review and meta-analysis

Petrelli, Fausto; Ghidini, Michele; Sgroi, Giovanni; Vavassori, Ivano; Petrò, Daniela; Cabiddu, Mary; Aiolfi, Alberto; Bonitta, Gianluca; Zaniboni, Alberto; Rausa, Emanuele

doi:10.1007/s00595-020-02192-3

Cited by 11 publications

References 153 publications

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“…In patients with cancer, the strongest predictor of early and late ICU mortality is the presence of metastatic cancer. Red blood cell transfusions are a negative predictor of early mortality, as already known [61]. Interestingly, transfusions were found to be the strongest predictor of late mortality, more than one year after admission to the ICU, for patients with cancer.…”

Section: Discussionsupporting

confidence: 55%

“…Interestingly, transfusions were found to be the strongest predictor of late mortality, more than one year after admission to the ICU, for patients with cancer. Red cell transfusions in patients with cancer not only increase the risk of death but also the risk of relapse [61]. Unfortunately, information regarding transfusion (red blood cells, plasma, and platelets) is missing in a significant number of patients, whereas in MIMIC-III, this information is scattered across two different information systems that collect data (Metavision and Carevue), and again, a significant number of data points are missing.…”

Section: Discussionmentioning

confidence: 99%

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Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

Danilatou

Nikolakakis²,

Antonakaki³

et al. 2022

IJMS

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Intensive care unit (ICU) patients with venous thromboembolism (VTE) and/or cancer suffer from high mortality rates. Mortality prediction in the ICU has been a major medical challenge for which several scoring systems exist but lack in specificity. This study focuses on two target groups, namely patients with thrombosis or cancer. The main goal is to develop and validate interpretable machine learning (ML) models to predict early and late mortality, while exploiting all available data stored in the medical record. To this end, retrospective data from two freely accessible databases, MIMIC-III and eICU, were used. Well-established ML algorithms were implemented utilizing automated and purposely built ML frameworks for addressing class imbalance. Prediction of early mortality showed excellent performance in both disease categories, in terms of the area under the receiver operating characteristic curve (AUC−ROC): VTE-MIMIC-III 0.93, eICU 0.87, cancer-MIMIC-III 0.94. On the other hand, late mortality prediction showed lower performance, i.e., AUC−ROC: VTE 0.82, cancer 0.74–0.88. The predictive model of early mortality developed from 1651 VTE patients (MIMIC-III) ended up with a signature of 35 features and was externally validated in 2659 patients from the eICU dataset. Our model outperformed traditional scoring systems in predicting early as well as late mortality. Novel biomarkers, such as red cell distribution width, were identified.

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Section: Discussionsupporting

confidence: 55%

Section: Discussionmentioning

confidence: 99%

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

Danilatou

Nikolakakis²,

Antonakaki³

et al. 2022

IJMS

View full text Add to dashboard Buy / Rent full text

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“…However, transfusion burden has been identified as an independent predictor for poor outcome in several prospective studies carried out in cancer and noncancer patients. [30][31][32][33] Number of transfusions at transplant is also an independent predictor for graft failure and survival in the liver transplant setting. 34 The immunomodulatory effect by blood products has been largely evoked as the mechanism underlying this association.…”

Section: Discussionmentioning

confidence: 99%

ABO Mismatch in Allogeneic Hematopoietic Stem Cell Transplant: Effect on Short- and Long-term Outcomes

Valentini¹,

Metafuni²,

Gallo

et al. 2021

Transplantation Direct

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“…In general, several cohort studies reported increased mortality and LOS after RBCT [ 36 ]. Of note, in patients with cancer undergoing curative surgery, RBCT have also been associated with increased risk of death and relapse [ 37 ].…”

Section: Discussionmentioning

confidence: 99%

Intraoperative transfusion practices and perioperative outcome in the European elderly: A secondary analysis of the observational ETPOS study

et al. 2022

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The demographic development suggests a dramatic growth in the number of elderly patients undergoing surgery in Europe. Most red blood cell transfusions (RBCT) are administered to older people, but little is known about perioperative transfusion practices in this population. In this secondary analysis of the prospective observational multicentre European Transfusion Practice and Outcome Study (ETPOS), we specifically evaluated intraoperative transfusion practices and the related outcomes of 3149 patients aged 65 years and older. Enrolled patients underwent elective surgery in 123 European hospitals, received at least one RBCT intraoperatively and were followed up for 30 days maximum. The mean haemoglobin value at the beginning of surgery was 108 (21) g/l, 84 (15) g/l before transfusion and 101 (16) g/l at the end of surgery. A median of 2 [1–2] units of RBCT were administered. Mostly, more than one transfusion trigger was present, with physiological triggers being preeminent. We revealed a descriptive association between each intraoperatively administered RBCT and mortality and discharge respectively, within the first 10 postoperative days but not thereafter. In our unadjusted model the hazard ratio (HR) for mortality was 1.11 (95% CI: 1.08–1.15) and the HR for discharge was 0.78 (95% CI: 0.74–0.83). After adjustment for several variables, such as age, preoperative haemoglobin and blood loss, the HR for mortality was 1.10 (95% CI: 1.05–1.15) and HR for discharge was 0.82 (95% CI: 0.78–0.87). Pre-operative anaemia in European elderly surgical patients is undertreated. Various triggers seem to support the decision for RBCT. A closer monitoring of elderly patients receiving intraoperative RBCT for the first 10 postoperative days might be justifiable. Further research on the causal relationship between RBCT and outcomes and on optimal transfusion strategies in the elderly population is warranted. A thorough analysis of different time periods within the first 30 postoperative days is recommended.

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Red blood cell transfusions and the survival in patients with cancer undergoing curative surgery: a systematic review and meta-analysis

Cited by 11 publications

References 153 publications

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

Outcome Prediction in Critically-Ill Patients with Venous Thromboembolism and/or Cancer Using Machine Learning Algorithms: External Validation and Comparison with Scoring Systems

ABO Mismatch in Allogeneic Hematopoietic Stem Cell Transplant: Effect on Short- and Long-term Outcomes

Intraoperative transfusion practices and perioperative outcome in the European elderly: A secondary analysis of the observational ETPOS study

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