Observational studyBMC infectious diseases2021
A predictive nomogram for mortality of cancer patients with invasive candidiasis: a 10-year study in a cancer center of North China.
Observational study in BMC infectious diseases, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
10 citing papers in PubMed, 15 citations in OpenAlex.
- Construction and validation of a predictive in-hospital mortality nomogram in patients with staphylococcus aureus bloodstream infection.Scientific reports · 2025Article
- In vitro and in vivo antifungal activity of Minocycline albumin nanoparticles in combination with fluconazole against azole-resistant Candida spp.BMC microbiology · 2025Article
- Predictive nomogram for early detection of invasive fungal disease deterioration --- a 10-year retrospective cohort study.BMC infectious diseases · 2025Article
- PediatricJournal of fungi (Basel, Switzerland) · 2025Article
- 30-day mortality in invasive candidiasis and candidemia in a multidisciplinary hospital in Moscow, Russia.Current medical mycology · 2025Article
- Enhancing prognostic prediction of invasive candidiasis among cancer patients with a serum C5a-based scoring model.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2024Article
- Establishment of a risk classifier to predict the in-hospital death risk of nosocomial fungal infections in cancer patients.BMC infectious diseases · 2023Observational
- Relationships between Secreted Aspartyl Proteinase 2 and General Control Nonderepressible 4 gene in the Candida albicans resistant to itraconazole under planktonic and biofilm conditions.Brazilian journal of microbiology : [publication of the Brazilian Society for Microbiology] · 2023Article
- Clinical characteristics of bloodstream infections in adult patients with solid tumours and a nomogram for mortality prediction: a 5-year case-controlled retrospective study in a tertiary-level hospital.Frontiers in cellular and infection microbiology · 2023Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 3 institutions in 1 country.
Funding
Abstract
backgroundInvasive candidiasis is the most common fungal disease among hospitalized patients and continues to be a major cause of mortality. Risk factors for mortality have been studied previously but rarely developed into a predictive nomogram, especially for cancer patients. We constructed a nomogram for mortality prediction based on a retrospective review of 10 years of data for cancer patients with invasive candidiasis.
methodsClinical data for cancer patients with invasive candidiasis during the period of 2010-2019 were studied; the cases were randomly divided into training and validation cohorts. Variables in the training cohort were subjected to a predictive nomogram based on multivariate logistic regression analysis and a stepwise algorithm. We assessed the performance of the nomogram through the area under the receiver operating characteristic (ROC) curve (AUC) and decision curve analysis (DCA) in both the training and validation cohorts.
resultsA total of 207 cases of invasive candidiasis were examined, and the crude 30-day mortality was 28.0%. Candida albicans (48.3%) was the predominant species responsible for infection, followed by the Candida glabrata complex (24.2%) and Candida tropicalis (10.1%). The training and validation cohorts contained 147 and 60 cases, respectively. The predictive nomogram consisted of bloodstream infections, intensive care unit (ICU) admitted > 3 days, no prior surgery, metastasis and no source control. The AUCs of the training and validation cohorts were 0.895 (95% confidence interval [CI], 0.846-0.945) and 0.862 (95% CI, 0.770-0.955), respectively. The net benefit of the model performed better than "treatment for all" in DCA and was also better for opting low-risk patients out of treatment than "treatment for none" in opt-out DCA.
conclusionCancer patients with invasive candidiasis exhibit high crude mortality. The predictive nomogram established in this study can provide a probability of mortality for a given patient, which will be beneficial for therapeutic strategies and outcome improvement.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.