Evidence map›Paper›PMID 38012615›Full record

ArticleBMC women's health2023

Diagnostic and pre-treatment intervals among patients with cervical cancer attending care at the Uganda Cancer Institute: a cross-sectional study.

Jackie Lalam Lacika, Henry Wabinga, Joseph Kagaayi, Ronald Opito, Christopher Garimoi Orach, Amos Deogratius Mwaka

Open access · goldAbstract read
In one paragraph

Article in BMC women's health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.1field-weighted citation impact, top 21% 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

8 citing papers in PubMed, 5 citations in OpenAlex.

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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

6 authors at 2 institutions in 1 country.

Jackie Lalam LacikaDepartment of Community Health & Behavioural Sciences, School of Public Health, College of Health Sciences, Makerere University, P.O Box 7072, Kampala, Uganda.
Henry WabingaDepartment of Pathology, School of Biomedical Sciences, College of Health Sciences, Makerere University, P.O Box 7072, Kampala, Uganda.
Joseph KagaayiDepartment of Community Health & Behavioural Sciences, School of Public Health, College of Health Sciences, Makerere University, P.O Box 7072, Kampala, Uganda.
Ronald OpitoDepartment of Public Health, School of Health Sciences, Soroti University, P.O Box 211, Soroti, Uganda.
Christopher Garimoi OrachDepartment of Community Health & Behavioural Sciences, School of Public Health, College of Health Sciences, Makerere University, P.O Box 7072, Kampala, Uganda.
Amos Deogratius MwakaDepartment of Medicine, School of Medicine, College of Health Sciences, Makerere University, P.O Box 7072, Kampala, Uganda. mgratius@gmail.com.
Makerere University · UGSoroti University · UG

Funding

Medical Research Council Not Applicable
6 · The paper itself

Abstract

backgroundMajority of patients with cervical cancer in the low- and middle-income countries experience long diagnostic and pre-treatment intervals. This study sought to determine the factors associated with the diagnostic and pre-treatment intervals among patients with cervical cancer.

methodsThis was a cross-sectional study conducted at the Uganda Cancer Institute (UCI) during October 2019 to January 2020. Patients aged ≥ 18 years with histological diagnosis of cervical cancer were consecutively sampled. Data were collected using a pre-tested semi-structured questionnaire and a data abstraction form. Diagnostic intervals, defined as the time between first visit of a patient to a primary healthcare provider to time of getting confirmed diagnosis, of ≤ 3 months was defined as early & >3 months as late. Pre-treatment intervals, which is the time from histological diagnosis to starting cancer chemo-radiotherapy of ≤ 1 month was defined as early and > 1 month as late. Data were analysed using STATA version 14.0. We used modified Poisson regression models with robust variance to determine socio-demographic and clinical factors associated with the intervals.

resultsThe mean age of the participants was 50.0 ± 11.7 years. The median diagnostic and pre-treatment intervals were 3.1 (IQR: 1.4-8.2) months and 2.4 (IQR: 1.2-4.1) months respectively. Half of the participants, 49.6% (200/403) were diagnosed early; one in 5 patients, 20.1% (81/403) promptly (within one month) initiated cancer chemo-radiotherapy. Participants more likely to be diagnosed early included those referred from district hospitals (level 5) (aPR = 2.29; 95%CI: 1.60-3.26) and with squamous cell carcinomas (aPR = 1.55; 95%CI: 1.07-2.23). Participants more likely to be diagnosed late included those who first discussed their symptoms with relatives, (aPR = 0.77; 95%CI: (0.60-0.98), had > 2 pre-referral visits (aPR = 0.75; 95%CI (0.61-0.92), and had advanced stage (stages 3 or 4) (aPR = 0.68; 95%CI: 0.55-0.85). Participants more likely to initiate cancer chemo-radiotherapy early included older patients (≥ 60 years) (aPR = 2.44; 95%CI: 1.18-5.03). Patients likely to start treatment late were those who had ≥2 pre-referral visits  (aPR = 0.63; 95%CI: 0.41-0.98) and those that took 3 - 6 months with symptoms before seeking healthcare (aPR = 0.52;95%CI: 0.29 - 0.95).

conclusionInterventions to promote prompt health-seeking and early diagnosis of cervical cancer need to target primary healthcare facilities and aim to enhance capacity of primary healthcare professionals to promptly initiate diagnostic investigations. Patients aged < 60 years require targeted interventions to promote prompt initiation of chemo-radiation therapy.

Indexed as

Uterine Cervical NeoplasmsAdultCross-Sectional StudiesFemaleHumansMiddle AgedReferral and ConsultationSurveys and QuestionnairesUgandaAdvanced stageCervical cancerDiagnostic intervalsPre-treatment intervals

Identifiers

PMID38012615
PMCPMC10683271
OpenAlexW4389040005

What OpenQuestion holds

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LicenceCC BY
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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.