Evidence map›Paper›PMID 34234252›Full record

ArticleScientific reports2021

Mixed and nonvaccine high risk HPV types are associated with higher mortality in Black women with cervical cancer.

Rachelle P Mendoza, Tahmineh Haidary, Elmer Gabutan, Ying Yin Zhou, Zaheer Bukhari, Courtney Connelly, Wen-Ching Lee, Yi-Chun Lee, Raj Wadgaonkar, Raag Agrawal and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.1field-weighted citation impact, top 12% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed, 18 citations in OpenAlex.

  1. Iranian journal of basic medical sciences · 2026
    Article
  2. Review
  3. Article
  4. Article
  5. Article
  6. Observational
  7. Review
  8. Review
  9. Review
  10. Updates on HPV Vaccination.Diagnostics (Basel, Switzerland) · 2023
    Review
  11. Article
  12. Article
  13. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

Rachelle P MendozaDepartment of Pathology, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, 11203, USA.
Tahmineh HaidaryDepartment of Pathology, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, 11203, USA.
Elmer GabutanDepartment of Medicine, State University of New York, Downstate Health Sciences University, Brooklyn, NY, 11203, USA.
Ying Yin ZhouDepartment of Obstetrics and Gynecology, State University of New York, Downstate Health Sciences University, Brooklyn, NY, 11203, USA.
Zaheer BukhariDepartment of Pathology, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, 11203, USA.
Courtney ConnellyDepartment of Pathology, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, 11203, USA.
Wen-Ching LeeDepartment of Obstetrics and Gynecology, State University of New York, Downstate Health Sciences University, Brooklyn, NY, 11203, USA.
Yi-Chun LeeDepartment of Obstetrics and Gynecology, State University of New York, Downstate Health Sciences University, Brooklyn, NY, 11203, USA.
Raj WadgaonkarDepartment of Medicine, State University of New York, Downstate Health Sciences University, Brooklyn, NY, 11203, USA.
Raag AgrawalDepartment of Pathology, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, 11203, USA.
M A HaseebDepartment of Pathology, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, 11203, USA.
Raavi GuptaDepartment of Pathology, State University of New York, Downstate Health Sciences University, 450 Clarkson Avenue, Brooklyn, NY, 11203, USA. raavi.gupta@downstate.edu.
State University of New York · USSUNY Downstate Health Sciences University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We studied the incidence of HPV genotypes in mostly Black women with cervical carcinoma and correlated histopathologic tumor characteristics, immune markers and clinical data with survival. Disease-free survival (DFS) and overall survival (OS) were recorded for 60 months post-diagnosis. Fifty four of the 60 (90%) patients were Black and 36 (60%) were < 55 years of age. Of the 40 patients with typeable HPV genotypes, 10 (25%) had 16/18 HPV genotypes, 30 (75%) had one of the non-16/18 HPV genotypes, and 20 (50%) had one of the 7 genotypes (35, 39, 51, 53, 56, 59 and 68) that are not included in the nonavalent vaccine. Mixed HPV infections (≥ 2 types) were found in 11/40 (27.5%) patients. Patients infected with non-16/18 genotypes, including the most common genotype, HPV 35, had significantly shorter DFS and OS. PD-L1 (p = 0.003), MMR expression (p = 0.01), clinical stage (p = 0.048), histologic grade (p = 0.015) and mixed HPV infection (p = 0.026) were independent predictors of DFS. A remarkably high proportion of cervical cancer cells in our patients expressed PD-L1 which opens the possibility of the use of immune checkpoint inhibitors to treat these cancers. Exclusion of the common HPV genotypes from the vaccine exacerbates mortality from cervical cancer in underserved Black patients.

Indexed as

Black or African AmericanPapillomaviridaeAdultAgedBiomarkers, TumorCoinfectionDisease SusceptibilityFemaleGenotypeHumansImmunohistochemistryImmunophenotypingMiddle AgedNeoplasm GradingNeoplasm StagingPapillomavirus InfectionsBiomarkers, TumorPapillomavirus Vaccines

Identifiers

PMID34234252
PMCPMC8263581
OpenAlexW3182571978

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.