1
|
Senders JT, Muskens IS, Cote DJ, Goldhaber
NH, Dawood HY, Gormley WB, Broekman MLD and Smith TR: Thirty-Day
outcomes after craniotomy for primary malignant brain tumors: A
national surgical quality improvement program analysis.
Neurosurgery. 83:1249–1259. 2018. View Article : Google Scholar : PubMed/NCBI
|
2
|
De la Garza-Ramos R, Kerezoudis P, Tamargo
RJ, Brem H, Huang J and Bydon M: Surgical complications following
malignant brain tumor surgery: An analysis of 2002–2011 data. Clin
Neurol Neurosurg. 140:6–10. 2016. View Article : Google Scholar : PubMed/NCBI
|
3
|
Lonjaret L, Guyonnet M, Berard E,
Vironneau M, Peres F, Sacrista S, Ferrier A, Ramonda V, Vuillaume
C, Roux FE, et al: Postoperative complications after craniotomy for
brain tumor surgery. Anaesth Crit Care Pain Med. 36:213–218. 2017.
View Article : Google Scholar : PubMed/NCBI
|
4
|
Writing Committee for the VISION Study
Investigators, . Devereaux PJ, Biccard BM, Sigamani A, Xavier D,
Chan MTV, Srinathan SK, Walsh M, Abraham V, Pearse R, et al:
Association of postoperative High-Sensitivity troponin levels with
myocardial injury and 30-Day mortality among patients undergoing
noncardiac surgery. JAMA. 317:1642–1651. 2017. View Article : Google Scholar : PubMed/NCBI
|
5
|
Fritz BA, Cui Z, Zhang M, He Y, Chen Y,
Kronzer A, Ben Abdallah A, King CR and Avidan MS: Deep-learning
model for predicting 30-day postoperative mortality. Br J Anaesth.
123:688–695. 2019. View Article : Google Scholar : PubMed/NCBI
|
6
|
Watters DA, Hollands MJ, Gruen RL, Maoate
K, Perndt H, McDougall RJ, Morriss WW, Tangi V, Casey KM and
McQueen KA: Perioperative mortality rate (POMR): A global indicator
of access to safe surgery and anaesthesia. World J Surg.
39:856–864. 2015. View Article : Google Scholar : PubMed/NCBI
|
7
|
Lochte BC, Carroll KT, Hirshman B, Lanman
T, Carter B and Chen CC: Smoking as a risk factor for
postcraniotomy 30-Day mortality. World Neurosurg. 127:e400–e406.
2019. View Article : Google Scholar : PubMed/NCBI
|
8
|
Williams M, Treasure P, Greenberg D,
Brodbelt A and Collins P: Surgeon volume and 30 day mortality for
brain tumours in England. Br J Cancer. 115:1379–1382. 2016.
View Article : Google Scholar : PubMed/NCBI
|
9
|
Dikmen S, Machamer J, Manley GT, Yuh EL,
Nelson LD and Temkin NR; TRACK-TBI Investigators, : Functional
status examination versus glasgow outcome scale extended as outcome
measures in traumatic brain injuries: How do they compare? J
Neurotrauma. 36:2423–2429. 2019. View Article : Google Scholar : PubMed/NCBI
|
10
|
Ois A, Vivas E, Figueras-Aguirre G,
Guimaraens L, Cuadrado-Godia E, Avellaneda C, Bertran-Recasens B,
Rodríguez-Campello A, Gracia MP, Villalba G, et al: Misdiagnosis
worsens prognosis in subarachnoid hemorrhage with good hunt and
hess score. Stroke. 50:3072–3076. 2019. View Article : Google Scholar : PubMed/NCBI
|
11
|
Khalil H, Aldaajani ZF, Aldughmi M,
Al-Sharman A, Mohammad T, Mehanna R, El-Jaafary SI, Dahshan A, Ben
Djebara M, Kamel WA, et al: Validation of the arabic version of the
movement disorder Society-Unified parkinson's disease rating scale.
Mov Disord. 37:826–841. 2022. View Article : Google Scholar : PubMed/NCBI
|
12
|
Gittleman H, Lim D, Kattan MW, Chakravarti
A, Gilbert MR, Lassman AB, Lo SS, Machtay M, Sloan AE, Sulman EP,
et al: An independently validated nomogram for individualized
estimation of survival among patients with newly diagnosed
glioblastoma: NRG Oncology RTOG 0525 and 0825. Neuro Oncol.
19:669–677. 2017.PubMed/NCBI
|
13
|
Mijderwijk HJ, Nieboer D, Incekara F,
Berger K, Steyerberg EW, van den Bent MJ, Reifenberger G, Hänggi D,
Smits M, Senft C, et al: Development and external validation of a
clinical prediction model for survival in patients with IDH
wild-type glioblastoma. J Neurosurg. Jan 14–2022.(Epub ahead of
print). View Article : Google Scholar : PubMed/NCBI
|
14
|
Wang Z, Gao L, Guo X, Feng C, Lian W, Deng
K and Xing B: Development of a nomogram with alternative splicing
signatures for predicting the prognosis of glioblastoma: A study
based on Large-Scale sequencing data. Front Oncol. 10:12572020.
View Article : Google Scholar : PubMed/NCBI
|
15
|
Molinaro AM, Wrensch MR, Jenkins RB and
Eckel-Passow JE: Statistical considerations on prognostic models
for glioma. Neuro Oncol. 18:609–623. 2016. View Article : Google Scholar : PubMed/NCBI
|
16
|
Li N, Mo Y, Huang C, Han K, He M, Wang X,
Wen J, Yang S, Wu H, Dong F, et al: A clinical semantic and
radiomics nomogram for predicting brain invasion in WHO grade II
meningioma based on tumor and Tumor-to-Brain interface features.
Front Oncol. 11:7521582021. View Article : Google Scholar : PubMed/NCBI
|
17
|
Zhang J, Yao K, Liu P, Liu Z, Han T, Zhao
Z, Cao Y, Zhang G, Zhang J, Tian J and Zhou J: A radiomics model
for preoperative prediction of brain invasion in meningioma
non-invasively based on MRI: A multicentre study. Ebiomedicine.
58:1029332020. View Article : Google Scholar : PubMed/NCBI
|
18
|
Pietrantonio F, Aprile G, Rimassa L,
Franco P, Lonardi S, Cremolini C, Biondani P, Sbicego EL,
Pasqualetti F, Tomasello G, et al: A new nomogram for estimating
survival in patients with brain metastases secondary to colorectal
cancer. Radiother Oncol. 117:315–321. 2015. View Article : Google Scholar : PubMed/NCBI
|
19
|
Marko NF, Xu Z, Gao T, Kattan MW and Weil
RJ: Predicting survival in women with breast cancer and brain
metastasis: A nomogram outperforms current survival prediction
models. Cancer. 118:3749–3757. 2012. View Article : Google Scholar : PubMed/NCBI
|
20
|
Cheng S, Yang L, Dai X, Wang J and Han X:
The risk and prognostic factors for brain metastases in esophageal
cancer patients: An analysis of the SEER database. BMC Cancer.
21:10572021. View Article : Google Scholar : PubMed/NCBI
|
21
|
Zhai Y, Bai J, Li M, Wang S, Li C, Wei X
and Zhang Y: A nomogram to predict the progression-free survival of
clival chordoma. J Neurosurg. 134:144–152. 2019. View Article : Google Scholar : PubMed/NCBI
|
22
|
Dasgupta A, Gupta T, Pungavkar S, Shirsat
N, Epari S, Chinnaswamy G, Mahajan A, Janu A, Moiyadi A, Kannan S,
et al: Nomograms based on preoperative multiparametric magnetic
resonance imaging for prediction of molecular subgrouping in
medulloblastoma: Results from a radiogenomics study of 111
patients. Neuro Oncol. 21:115–124. 2019. View Article : Google Scholar : PubMed/NCBI
|
23
|
Zhang D, Zhuo H, Yang G, Huang H, Li C,
Wang X, Zhao S, Moliterno J and Zhang Y: Postoperative pneumonia
after craniotomy: Incidence, risk factors and prediction with a
nomogram. J Hosp Infect. 105:167–175. 2020. View Article : Google Scholar : PubMed/NCBI
|
24
|
Zhang J, Li YI, Pieters TA, Towner J, Li
KZ, Al-Dhahir MA, Childers F and Li YM: Sepsis and septic shock
after craniotomy: Predicting a significant patient safety and
quality outcome measure. PLoS One. 15:e2352732020.
|
25
|
Groenwold RH, White IR, Donders AR,
Carpenter JR, Altman DG and Moons KG: Missing covariate data in
clinical research: When and when not to use the missing-indicator
method for analysis. CMAJ. 184:1265–1269. 2012. View Article : Google Scholar : PubMed/NCBI
|
26
|
White IR, Royston P and Wood AM: Multiple
imputation using chained equations: Issues and guidance for
practice. Stat Med. 30:377–399. 2011. View Article : Google Scholar : PubMed/NCBI
|
27
|
Friedman J, Hastie T and Tibshirani R:
Regularization paths for generalized linear models via coordinate
descent. J Stat Softw. 33:1–22. 2010. View Article : Google Scholar : PubMed/NCBI
|
28
|
Kidd AC, McGettrick M, Tsim S, Halligan
DL, Bylesjo M and Blyth KG: Survival prediction in mesothelioma
using a scalable Lasso regression model: Instructions for use and
initial performance using clinical predictors. BMJ Open Respir Res.
5:e0002402018. View Article : Google Scholar : PubMed/NCBI
|
29
|
Della Rosa PA, Miglioli C, Caglioni M,
Tiberio F, Mosser KHH, Vignotto E, Canini M, Baldoli C, Falini A,
Candiani M and Cavoretto P: A hierarchical procedure to select
intrauterine and extrauterine factors for methodological validation
of preterm birth risk estimation. BMC Pregnancy Childbirth.
21:3062021. View Article : Google Scholar : PubMed/NCBI
|
30
|
Roh J, Jung J, Lee Y, Kim SW, Pak HK, Lee
AN, Lee J, Cho J, Cho H, Yoon DH, et al: Risk stratification using
multivariable fractional polynomials in diffuse large B-Cell
lymphoma. Front Oncol. 10:3292020. View Article : Google Scholar : PubMed/NCBI
|
31
|
Weng ZA, Huang XX, Deng D, Yang ZG, Li SY,
Zang JK, Li YF, Liu YF, Wu YS, Zhang TY, et al: A new nomogram for
predicting the risk of intracranial hemorrhage in acute ischemic
stroke patients after intravenous thrombolysis. Front Neurol.
13:7746542022. View Article : Google Scholar : PubMed/NCBI
|
32
|
Alba AC, Agoritsas T, Walsh M, Hanna S,
Iorio A, Devereaux PJ, McGinn T and Guyatt G: Discrimination and
calibration of clinical prediction models: Users' guides to the
medical literature. JAMA. 318:1377–1384. 2017. View Article : Google Scholar : PubMed/NCBI
|
33
|
Mehta HB, Mehta V, Girman CJ, Adhikari D
and Johnson ML: Regression coefficient-based scoring system should
be used to assign weights to the risk index. J Clin Epidemiol.
79:22–28. 2016. View Article : Google Scholar : PubMed/NCBI
|
34
|
Collins GS, Reitsma JB, Altman DG and
Moons KG: Transparent reporting of a multivariable prediction model
for individual prognosis or diagnosis (TRIPOD): The TRIPOD
statement. BMJ. 350:g75942015. View Article : Google Scholar : PubMed/NCBI
|
35
|
Hu X, Martinez-Ledesma E, Zheng S, Kim H,
Barthel F, Jiang T, Hess KR and Verhaak RGW: Multigene signature
for predicting prognosis of patients with 1p19q co-deletion diffuse
glioma. Neuro Oncol. 19:786–795. 2017. View Article : Google Scholar : PubMed/NCBI
|
36
|
Zhang Y, Ma W, Fan W, Ren C, Xu J, Zeng F,
Bao Z, Jiang T and Zhao Z: Comprehensive transcriptomic
characterization reveals core genes and module associated with
immunological changes via 1619 samples of brain glioma. Cell Death
Dis. 12:11402021. View Article : Google Scholar : PubMed/NCBI
|
37
|
Zheng Y, Ji Q, Xie L, Wang C, Yu CN, Wang
YL, Jiang J, Chen F and Li WB: Ferroptosis-related gene signature
as a prognostic marker for lower-grade gliomas. J Cell Mol Med.
25:3080–3090. 2021. View Article : Google Scholar : PubMed/NCBI
|
38
|
Wang X, Gao M, Ye J, Jiang Q, Yang Q,
Zhang C, Wang S, Zhang J, Wang L, Wu J, et al: An immune
Gene-Related Five-lncRNA signature for to predict glioma prognosis.
Front Genet. 11:6120372020. View Article : Google Scholar : PubMed/NCBI
|
39
|
Yun D, Wang X, Wang W, Ren X, Li J, Wang
X, Liang J, Liu J, Fan J, Ren X, et al: A novel prognostic
signature based on glioma essential Ferroptosis-Related genes
predicts clinical outcomes and indicates treatment in glioma. Front
Oncol. 12:8977022022. View Article : Google Scholar : PubMed/NCBI
|
40
|
Missios S, Kalakoti P, Nanda A and Bekelis
K: Craniotomy for glioma resection: A predictive model. World
Neurosurg. 83:957–964. 2015. View Article : Google Scholar : PubMed/NCBI
|
41
|
Jia Z, Yan Y, Wang J, Yang H, Zhan H, Chen
Q, He Y and Hu Y: Development and validation of prognostic nomogram
in patients with WHO grade III meningioma: A retrospective cohort
study based on SEER database. Front Oncol. 11:7199742021.
View Article : Google Scholar : PubMed/NCBI
|
42
|
Zhang GJ, Liu XY and You C: Clinical
factors and outcomes of atypical meningioma: A Population-Based
study. Front Oncol. 11:6766832021. View Article : Google Scholar : PubMed/NCBI
|
43
|
Xiong Y, Cao H, Zhang Y, Pan Z, Dong S,
Wang G, Wang F and Li X: Nomogram-Predicted survival of breast
cancer brain metastasis: A SEER-Based population study. World
Neurosurg. 128:e823–e834. 2019. View Article : Google Scholar : PubMed/NCBI
|
44
|
Zindler JD, Jochems A, Lagerwaard FJ,
Beumer R, Troost EGC, Eekers DBP, Compter I, van der Toorn PP,
Essers M, Oei B, et al: Individualized early death and long-term
survival prediction after stereotactic radiosurgery for brain
metastases of non-small cell lung cancer: Two externally validated
nomograms. Radiother Oncol. 123:189–194. 2017. View Article : Google Scholar : PubMed/NCBI
|
45
|
Shen H, Deng G, Chen Q and Qian J: The
incidence, risk factors and predictive nomograms for early death of
lung cancer with synchronous brain metastasis: A retrospective
study in the SEER database. BMC Cancer. 21:8252021. View Article : Google Scholar : PubMed/NCBI
|
46
|
Yao Z, Zheng Z, Ke W, Wang R, Mu X, Sun F,
Wang X, Garg S, Shi W, He Y and Liu Z: Prognostic nomogram for
bladder cancer with brain metastases: A National Cancer Database
analysis. J Transl Med. 17:4112019. View Article : Google Scholar : PubMed/NCBI
|
47
|
Nieder C, Hintz M and Grosu AL: Predicted
survival in patients with brain metastases from colorectal cancer:
Is a current nomogram helpful? Clin Neurol Neurosurg. 143:107–110.
2016. View Article : Google Scholar : PubMed/NCBI
|
48
|
Bodewes T, Pothof AB, Darling JD, Deery
SE, Jones DW, Soden PA, Moll FL and Schermerhorn ML: Preoperative
anemia associated with adverse outcomes after infrainguinal bypass
surgery in patients with chronic limb-threatening ischemia. J Vasc
Surg. 66:1775–1785.e2. 2017. View Article : Google Scholar : PubMed/NCBI
|
49
|
Kouyoumdjian A, Trepanier M, Al Shehhi R,
Cools-Lartigue J, Ferri LE, Lee L and Mueller CL: The effect of
preoperative anemia and perioperative transfusion on surgical
outcomes after gastrectomy for gastric cancer. J Surg Res.
259:523–531. 2021. View Article : Google Scholar : PubMed/NCBI
|
50
|
Faraoni D, DiNardo JA and Goobie SM:
Relationship between preoperative anemia and In-Hospital mortality
in children undergoing noncardiac surgery. Anesth Analg.
123:1582–1587. 2016. View Article : Google Scholar : PubMed/NCBI
|
51
|
Zhang X, Zhang F, Qiao W, Zhang X, Zhao Z
and Li M: Low hematocrit is a strong predictor of poor prognosis in
lung cancer patients. Biomed Res Int. 2018:68049382018.PubMed/NCBI
|
52
|
Lee DY, Chung EL, Guend H, Whelan RL,
Wedderburn RV and Rose KM: Predictors of mortality after emergency
colectomy for Clostridium difficile colitis: An analysis of
ACS-NSQIP. Ann Surg. 259:148–156. 2014. View Article : Google Scholar : PubMed/NCBI
|
53
|
Chung PJ, Carter TI, Burack JH, Tam S,
Alfonso A and Sugiyama G: Predicting the risk of death following
coronary artery bypass graft made simple: A retrospective study
using the American College of Surgeons National Surgical quality
improvement program database. J Cardiothorac Surg. 10:622015.
View Article : Google Scholar : PubMed/NCBI
|
54
|
Cagney DN, Martin AM, Catalano PJ, Redig
AJ, Lin NU, Lee EQ, Wen PY, Dunn IF, Bi WL, Weiss SE, et al:
Incidence and prognosis of patients with brain metastases at
diagnosis of systemic malignancy: A population-based study. Neuro
Oncol. 19:1511–1521. 2017. View Article : Google Scholar : PubMed/NCBI
|