Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan

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The cancer stage at presentation is related to survival evaluation and several factors determine stage. The aim of the study was to examine predictors covariates associated with cervical cancer stage at diagnosis and its impact on patient prognosis and survival. Methods: This retrospective cross-sectional study was carried out at Khartoum oncology hospital, Sudan. Participants were 239 cervical cancer patients diagnosed and treated between 2011-2015. Patients’ pathological and socio-demographic data were extracted from their medical files and survival times were calculated from follow-up. Chi-square, Kaplan-Meier, Log-rank test and Cox regression model were used to examine relationships between demographic and clinical variables and survival outcome. Results: The mean age of the participants was 56.91 years and the majority were ≥45 years. Cancer survival analysis showed that the stage at diagnosis had limited association with socio-demographic factors, except where patients reside. Multivariate regression using the Cox proportional hazard model confirmed strongly that stage (p=0.035), chemotherapy (p=0.000) and radiotherapy (p=0.001) were the most likely predictor covariates of patient prognosis and survival time. Conclusions: The results of this study suggest cancer stage at diagnosis and certain treatments are the most important factors impacting the prognosis and survival of patients with cervical cancer. Early detection and vaccination of women against HPV infection provide enormous opportunities for early diagnosis, more effective treatment and better chances of survival." } { "@context": "http://schema.org", "@type": "BreadcrumbList", "itemListElement": [ { "@type": "ListItem", "position": "1", "item": { "@id": "https://f1000research.com/", "name": "Home" } }, { "@type": "ListItem", "position": "2", "item": { "@id": "https://f1000research.com/browse/articles", "name": "Browse" } }, { "@type": "ListItem", "position": "3", "item": { "@id": "https://f1000research.com/articles/10-114/v2", "name": "Associated predictor covariates of cervical cancer stage and impact..." } } ] } Home Browse Associated predictor covariates of cervical cancer stage and impact... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Elgoraish A and Alnory A. Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.12688/f1000research.43590.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. Close Copy Citation Details Export Export Citation Sciwheel EndNote Ref. Manager Bibtex ProCite Sente EXPORT Select a format first Track Share ▬ ✚ Research Article Revised Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] Previously titled: Associated predictor covariates of cervical cancer and impact on survival at Khartoum oncology hospital, Sudan Amanda Elgoraish https://orcid.org/0000-0003-2420-3120 1 , Ahmed Alnory 2 Amanda Elgoraish https://orcid.org/0000-0003-2420-3120 1 , Ahmed Alnory 2 PUBLISHED 07 Oct 2022 Author details Author details 1 Epidemiology, Tropical Medicine Research Institute, National Centre for Research, Khartoum, Khartoum, P.O. Box 1304, Sudan 2 Applied Statistics and Demography, Faculty of Economics and Rural Development, University of Gezira, Medani, Gezira, P.O. Box 20, Sudan Amanda Elgoraish Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing Ahmed Alnory Roles: Conceptualization, Supervision, Writing – Review & Editing OPEN PEER REVIEW DETAILS REVIEWER STATUS This article is included in the Oncology gateway. Abstract Background: Cervical cancer can be invasive and advanced at diagnosis causing devastating suffering and premature death. The cancer stage at presentation is related to survival evaluation and several factors determine stage. The aim of the study was to examine predictors covariates associated with cervical cancer stage at diagnosis and its impact on patient prognosis and survival. Methods: This retrospective cross-sectional study was carried out at Khartoum oncology hospital, Sudan. Participants were 239 cervical cancer patients diagnosed and treated between 2011-2015. Patients’ pathological and socio-demographic data were extracted from their medical files and survival times were calculated from follow-up. Chi-square, Kaplan-Meier, Log-rank test and Cox regression model were used to examine relationships between demographic and clinical variables and survival outcome. Results: The mean age of the participants was 56.91 years and the majority were ≥45 years. Cancer survival analysis showed that the stage at diagnosis had limited association with socio-demographic factors, except where patients reside. Multivariate regression using the Cox proportional hazard model confirmed strongly that stage (p=0.035), chemotherapy (p=0.000) and radiotherapy (p=0.001) were the most likely predictor covariates of patient prognosis and survival time. Conclusions: The results of this study suggest cancer stage at diagnosis and certain treatments are the most important factors impacting the prognosis and survival of patients with cervical cancer. Early detection and vaccination of women against HPV infection provide enormous opportunities for early diagnosis, more effective treatment and better chances of survival. READ ALL READ LESS Keywords Cervical cancer, survival, stage, Cox model, Sudan Corresponding Author(s) Amanda Elgoraish ( [email protected] ) Close Corresponding author: Amanda Elgoraish Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2022 Elgoraish A and Alnory A. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. How to cite: Elgoraish A and Alnory A. Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.12688/f1000research.43590.2 ) First published: 15 Feb 2021, 10 :114 ( https://doi.org/10.12688/f1000research.43590.1 ) Latest published: 07 Oct 2022, 10 :114 ( https://doi.org/10.12688/f1000research.43590.2 ) Revised Amendments from Version 1 This new version of the article does not include any major changes in the shape and the contents of the original one. However, some small minor changes wording of the text have been made to meet clarifications of points raised by the peer-reviewers. This new version of the article does not include any major changes in the shape and the contents of the original one. However, some small minor changes wording of the text have been made to meet clarifications of points raised by the peer-reviewers. See the authors' detailed response to the review by Nazik Hammad See the authors' detailed response to the review by Elvynna Leong and Ong Sok King READ REVIEWER RESPONSES Introduction Cancer is a global public health problem, particularly in low- and middle-income countries, due to aging populations as well as broader social and environmental factors such as infectious diseases, education and ethnicity. 1 There are observed disparities in global cancer prognosis as mortality is higher among developing countries due to a lack of comprehensive early detection and effective medical care. 2 Cancer is a leading cause of death among women in both developing and developed countries and is increasing. 3 Women in developing countries develop the disease during their prime reproductive period and face more suffering from the disease complications and risk of death. 4 The most common cancers afflicting women are those of the breast and cervix. These cancers are closely related to sexual and reproductive behaviour in Woman. 4 Cervical cancer is a considerable cause of death among women in developing countries though it is preventable. It is, also, potentially curable if detected early and treated effectively. It is the second most commonly diagnosed cancer in women in developing countries. 4 In these countries, cancer mortality exceeds that of diseases related to death in pregnancy. However, there is clear diversity of trends among world regions, within regions and individual countries, in the incidence and mortality of cervical cancer. In Africa, there is a wide variation due to different exposure and disease susceptibility. 1 In Sub-Saharan Africa, the incidence is low but mortality rates are high due to advanced stage at presentation. 5 In Sudan, cervical cancer represents more than 16% of all cancer in women and 85% of cases are diagnosed at an advanced stage. 6 , 7 Cervical cancer is closely related to human papillomavirus (HPV) 16/18 infection and 78% of cases in the Sudan are diagnosed as invasive Lesions. 8 Moreover, the incidence and mortality rates of this invasive cervical cancer have increased during the last decade, especially among relatively young women. 3 This increase can be attributed to major changes in demography, economic and social factors, other disease risk factors and disease awareness. 9 Cancer burden and disparity among countries and people can be explained by prevalence, incidence and mortality, but the most direct measure of disease severity can only be provided by survival rates. 10 Early detection and prevention are the most effective ways to reduce premature death from cervical cancer; however, from a short-term perspective, immediate and effective treatment is the optimal solution. 11 Analysing cancer survival rates is an important way of discovering potential measures to be taken to improve the chances of better prognosis and survival. Cancer survival varies widely among different countries of the world due to differences in early detection and treatment modalities. By examining cancer survival from preventative measures and early detection, one can assess factors that have the greatest impact on cancer patient survival. Several studies have attempted to explain the relationships between patient survival and stage at diagnosis. These studies came to different conclusions about the strength and shape of these relationships and their impact. Researchers have a found significant association between the stage of cancer at diagnosis and survival. Socio-demographic attributes such as age, education, gender and ethnicity have also been shown to have some effects. 12 On other hand, differences in the type of treatment and quality of medical services might have an important effect on survival outcome. 11 Previous literature has shown the complexity of determining the drivers of international differences in the incidence and mortality of cervical cancer. It is most likely that each step in a patient’s journey to seek treatment contributes to some extent to these variations. 12 Many factors have been suggested to explain these variations; however, there is no complete agreement on potential predictor covariates that give overall explanations. Nevertheless, stage at diagnosis, tumor features and effective treatment have been postulated as the most widely accepted predictor covariates explaining degree and extent of their impact on prognosis and survival. For variations in cancer severity and survival, the stage at diagnosis remains the strongest predictor of cancer survival. 13 One can conclude that stage at diagnosis is related to survival evaluation and assessment. Several factors determine stage at diagnosis, including age, education, occupation, location, tumor features, availability and accessibility of adequate diagnostic and treatment facilities. 11 The stage at diagnosis is crucial to disease treatment as treatment plans are usually based on the stage of the disease. 14 The aim of this study was to examine predictor covariates associated with cervical cancer stage at diagnosis and its impact on cancer patient prognosis and survival. Methods Study design, setting and population This was a retrospective cross-sectional hospital-based study. It was carried out at Khartoum oncology hospital, Sudan, which is the only medical institution providing complete diagnostic and cancer treatment services, where more than 80% of all Sudan cancer patients are registered. 15 Available patient information was collected from the hospital’s medical records during the study period from 2011-2015. The target population of the study was patients with cervical cancer at Khartoum oncology hospital. To be included in the study, patients had to be between 18-79 years, be registered at the hospital, have complete medical records, have histopathologically confirmed cervical cancer and had received available treatment. Patients with incomplete medical records, unclear diagnosis and not treated at the hospital were excluded from the analysis. Written consent was obtained from the hospital to use participants’ data. No direct contact was made with patients during this data collection level. However, consent was obtained from participants during the active follow-up period. The total number of patients at the hospital during the study period who met inclusion criteria, and were included in the analysis, was 239. This sample size of randomly selected participants was calculated from the number of cervical cancer patients among all cancer patients at this hospital as follows: The formula n = 3.84 p(1-p)/(precision)2 Proportion = 0.044 (report of Federal Ministry of Health 2015), precision=0.026 with 95% CI n = 3.84*0.044(1-0.044)/(0.026) 2 = 239 Data collection and sources The study data collected from Khartoum oncology hospital patients’ medical files were checked and rechecked for accuracy, duplication, completeness and consistency by the researcher with continuous assistance from the hospital medical staff. Active follow-up was carried out during the year 2016 by the researcher by contacting patients or next of kin to ensure collection of needed information concerning patients survival status data(dead or alive). Moreover, a checklist was prepared by the researcher from the literature on cancer patients’ survival concerning socio-demographic and clinical factors affecting survival to assist in needed data collection. 16 , 33 Data collected were tabulated and coded according to the American Joint Committee on Cancer (AJCC) and the Union for International Cancer Control (UICC) TNM staging system for analysis. 17 Variables Data collected concerning socio-demographic characteristics and clinical status of patients included age at diagnosis, level of education, occupation, marital status, urban/rural residential area, tribe, menopausal status, cancer stage at diagnosis, tumor grade, tumor cell differentiation, histological subtype, treatment modalities, residence state and close family relation with previous disease experience. Dates of birth, death, loss to follow-up, diagnosis and survival times were checked by using other information provided by hospital medical and statistical staff. This information was clearly defined in medical terms concerning certificate of death, confirmation of diagnosis and calculation of survival time. Statistical analysis The statistical analysis is divided into two parts, descriptive statistics and regression analysis, using Stata version 11 (StataCorp, College Station, Texas) software. In the descriptive analysis, the visual presentation of data in tables and figures given, provides socio-demographic and clinical data in numbers, percentages, chi 2 and p-values and figures given provide clear indication of study population data distribution, relationships and associations. Then, important statistical conclusions were drawn. Statistical methods such as chi 2 , Kaplan-Meier, log-rank test and Cox regression were used to find out most prognostic factors associated with cancer patient survival. Socio-demographic variables and stage at diagnosis were tested by chi 2 . Stage, treatment, age and menopausal status were tested by log-rank test for equality. Socio-demographic variables, stage and treatment were tested by Cox regression. Stage was tested by Kaplan-Meier for survival rate between early and advanced levels. The analysis focuses on the stage at diagnosis as the most crucial prognostic predictor of cervical cancer patient survival. Results Descriptive statistics The total number of patients included in the analysis was 239 ( Table 1 ). 32 The median age of participants was 56.91 years (SE=0.88, 95%CI=55.17-85.65). The majority of participants 82.9% were ≥45 years old. In total, 94.6% of participants were married, 92.5% were unemployed, and 97.9% were illiterate and/or had no formal education. Most participants resided in the western, Khartoum and eastern states of Sudan. Table 1. Correlation between stage at diagnosis and socioeconomic variables among cervical cancer patients. Variables Total N(%) Stage N(%) Chi 2 , P-value Early Advanced Age group <30 4(1.7) 1(1.2) 3(1.9) 5.33, 0.255 30-44 37(15.5) 19(22.6) 18(11.6) 45-59 81(33.9) 27(32.1) 54(34.8) 60-74 91(38.1) 28(33.3) 63(40.6) ≥75 26(10.9) 9(10.7) 17(11.0) Urban/Rural status Rural 60(25.1) 20(23.8) 40(25.8) 0.12, 0.734 Urban 179(74.9) 64(76.2) 115(74.2) Resident states Khartoum 49(20.5) 11(13.1) 38(24.5) 11.23, 0.047 * Central 28(11.7) 16(19.0) 12(7.7) Northern 11(4.6) 2(2.4) 9(5.8) Eastern 32(13.4) 13(15.5) 19(12.3) Western 93(38.9) 33(39.3) 60(38.7) Southern 26(10.9) 9(10.7) 17(11.0) Tribes Non Arab descent African 150(62.8) 54(64.3) 96(61.9) 0.41, 0.814 Arab descent African 62(25.9) 22(26.2) 40(25.8) Other tribes 27(11.3) 8(9.5) 19(12.3) Education Illiterate 195(81.6) 72(85.7) 123(79.4) 1.59, 0.450 Low education 39(16.3) 11(13.1) 28(18.1) High education 5(2.1) 1(1.2) 4(2.6) Marital status Un married 13(5.4) 4(4.8) 9(5.8) 0.12, 0.734 Married 226(94.6) 80(95.2) 146(94.2) Occupation Non-employed 221(92.5) 77(91.7) 144(92.9) 0.12, 0.729 Employed 18(7.5) 7(8.3) 11(7.1) Menopause status Premenopausal 66(27.6) 28(33.3) 38(24.5) 2.12, 0.149 Postmenopausal 173(72.4) 56(66.7) 117(75.5) Parent relationship First degree relation 200(83.7) 75(89.3) 125(80.6) 3.37, 0.186 Relatives 22(9.2) 6(7.1) 16(10.3) Non relatives 17(7.1) 3(3.6) 14(9.0) Total 239 84(35.1) 155(64.9) * P-value<0.05 statistically significant association. The distribution frequency of cervical cancer cases, according to the tumor, node and metastasis (TNM) staging classification system demonstrated that the majority 64.9% of participants were of advanced stage (III & IV), invasive squamous cell carcinoma 98.0%, with a high probability of spreading to distant organs ( Table 2 ). Most of these patients’ tumors were of high grade and moderately to poorly differentiated cells. Furthermore, most of these patients had first-degree relations with previous disease history. Regarding treatment, 76.6% of these patients received radiotherapy, 57.3% chemotherapy, 10.5% hormone therapy and 6.3% surgery, alone or in combination with other therapies. Table 2. Test of equality of survival distribution for predictor variables. variable no. of subjects (%) Mean of survival time (months) 95% Confidence interval (CI) log rank (chi 2 ) P-value Stage a I 9(3.8) 16.06 12.46 to 19.65 33.49 0.000** II 75(31.4) 39.60 31.06 to 48.14 III 110(46.0) 28.27 22.88 to 33.67 IV 45(18.8) 13.09 6.55 to 19.62 Early 84(35.1) 40.49 32.28 to 48.71 7.91 0.005* Advanced 155(64.9) 23.77 19.32 to 28.23 Treatment Surgery 15(6.3) 34.64 20.31 to 48.98 0.47 0.491 Chemotherapy 137(57.3) 40.13 33.45 to 46.80 19.12 0.000** Radiotherapy 183(76.6) 33.86 28.4 to 39.31 3.63 0.057 Hormonal 25(10.5) 30.06 16.54 to 43.58 0.01 0.909 Age group <30 4(1.7) 29 28.9 to 29.01 10.13 0.038* 30-44 37(15.5) 27.22 17.31 to 37.17 45-59 81(33.9) 33.85 27.72 to 39.98 60-74 91(38.1) 29.26 21.83 to 36.68 ≥75 26(10.9) 11.92 7.01 to 16.82 Menopause status Premenopausal 66(27.6) 30.16 22.44 to 37.89 0.26 0.611 Postmenopausal 173(72.4) 31.06 25.42 to 36.71 Total 239 32.02 26.92 to 37.12 a % of invasive squamous cells carcinoma (98.0%), moderately to poorly differentiated cell (75.0%). There was no significant correlation between age group of participants and stage (p-value>0.05), though the most frequent group among advanced stage was ≥45 years group. There was no significant correlation between cancer stage at diagnosis and other socio-demographic variables except state of residence (chi 2 =11.23, df=5, p=0.047). This could be explained by the fact that Khartoum and nearby states have diagnostic and treatment facilities. Regression analysis The overall mean survival time after 60 months of follow-up from time of diagnosis to the end of the study period was 32.0 months (95% CI=26.92 to 37.12). The lowest mean survival time according to stage levels was recorded at 13.1 months for stage IV(95% CI=6.55 to 19.62) ( Table 2 ). Moreover, the log-rank test when performed to compare and explain survival distribution clearly showed highly statistically significant differences between various levels of the stage at diagnosis (chi 2 =33.49, df=3, p=0.000). Furthermore, the survival curve ( Figure 1 ) gives a visual description of these differences in survival times of different stage levels. The Kaplan-Meier and log-rank tests were performed according to early and advanced stages and indicated clear differences in survival time means between the two groups. A low mean survival time of 23.77 months at the advanced stage was observed compared to 40.49 months at the early stage. The chi 2 was 7.91, df=1 with p=0.005 ( Table 2 ). The graph of the two survival function curves was statistically different for the two groups. The lowest probability of 30% was recorded at the advanced stage ( Figure 1 ). Figure 1. Survival rate according to early and advanced stage. The Kaplan-Meier method and log-rank test were performed on the main four treatment therapies and only chemotherapy showed a highly statistically significant impact of chemotherapy on survival time. The chi 2 was 19.12, df=1 with p=0.000. As for age groups and survival times, the analysis revealed there was a clear difference in the age group ≥ 75 years. The log-rank test equals 10.13, df=4 and p=0.038. However, when the comparison was made according to their menopausal status, the results showed the difference was not statistically significant ( Table 2 ). Cox proportional hazard model The Cox proportional hazards model was performed in four phases. 18 In the first univariate model, single predictor covariates; stage, treatment modality (chemotherapy) and age were statistically significantly associated with survival time ( Table 3 ) while other factors were not. The hazard ratio of advanced stage at diagnosis was more than twice that at an earlier stage (HR=2.18 at 95% CI=1.24 to 3.83, p=0.007). This large difference was highly statistically significant with P-value <0.05. In the second multivariate (adjusted) model, all predictor covariates were included simultaneously which showed that advanced stage at diagnosis, treatment (chemotherapy and radiotherapy), state (eastern and western) and urban status were the only predictor covariates of survival time. Then, in the third model, all non-significant predictors, except age and surgery, were dropped from the model. The third model showed that stage and treatment (chemotherapy and radiotherapy) were statistically significant predictor covariates. The hazard ratio which measures the risk of dying from cervical cancer was nearly two times at the advanced stage compared to the early one (HR=1.84, at 95% CI=1.05 to 3.26, p=0.035). Other covariates were not statistically significant. However, the final multivariate model confirmed strongly stage, chemotherapy and radiotherapy, after age and surgery were dropped from the model, were the most likely predictor covariates of survival times and cervical cancer patient prognosis and survival outcome ( Table 4 ). Table 3. Univariate and multivariate regression models for association between survival time and predictor variables. Factor Univariate model Multivariate model HR(95%CI) P-value HR(95%CI) P-value Age 1.02(1.002 to 1.04) 0.027 * 1.02(0.99 to 1.05) 0.131 Stage Early 1(reference) - 1(reference) - Advanced 2.18(1.24 to 3.83) 0.007 * 1.84(1.003 to 3.39) 0.049 * Treatment Surgery 0.75(0.32 to 1.74) 0.497 0.52(0.19 to 1.38) 0.187 Chemotherapy 0.35(0.21 to 0.57) 0.000 ** 0.23(0.13 to 0.43) 0.000 ** Radiotherapy 0.57(0.32 to 1.03) 0.063 0.29(0.14 to 0.62) 0.001 ** Hormonal 1.04(0.52 to 2.11) 0.910 1.14(0.48 to 2.71) 0.768 Residence state Khartoum 1(reference) - 1(reference) - Central 0.51(0.19 to 1.30) 0.158 0.44(0.16 to 1.21) 0.111 Northern 1.44(0.59 to 3.53) 0.420 0.56(0.21 to 1.49) 0.243 Eastern 0.57(0.21 to 1.55) 0.267 0.23(0.06 to 0.82) 0.024 * Western 0.67(0.35 to 1.27) 0.221 0.46(0.22 to 0.99) 0.049 * Southern 0.97(0.44 to 2.14) 0.935 0.81(0.34 to 1.98) 0.649 Urban/Rural status Rural 1(reference) - 1(reference) - Urban 0.78(0.46 to 1.32) 0.356 0.35(0.18 to 0.69) 0.002 * Education Illiterate 1(reference) - 1(reference) - Low education 1.52(0.81 to 2.86) 0.189 1.67(0.82 to 3.40) 0.158 High education 1.55(0.38 to 6.39) 0.543 2.42(0.55 to 10.70) 0.246 Marital status Un married 1(reference) - 1(reference) - Married 1.69(0.52 to 5.45) 0.383 1.38(0.42 to 4.60) 0.593 Tribe Non Arab descent African 1(reference) - 1(reference) - Arab descent African 1.42(0.85 to 2.39) 0.183 1.67(0.76 to 2.71) 0.158 Others 0.91(0.39 to 2.16) 0.834 1.56(0.62 to 3.95) 0.343 Occupation Non employed 1(reference) - 1(reference) - Employed 0.98(0.39 to 2.44) 0.961 1.40(0.49 to 3.97) 0.526 Menopause status Premenopausal 1(reference) - 1(reference) - Postmenopausal 1.16(0.65 to 2.09) 0.615 0.65(0.25 to 1.73) 0.391 * P-value<0.05 statistically significant association. ** P-value<0.001 highly statistically significant association. Table 4. The final multivariate Cox model for association between survival time and predictor variables. Factor a HR(95%CI) P-value Stage Early 1(reference) Advanced 1.84(1.05 to 3.26) 0.035 * Chemotherapy 0.28(0.16 to 0.49) 0.000 ** Radiotherapy 0.33(0.17 to 0.64) 0.001 ** * P-value<0.05 statistically significant association. ** P-value<0.001 highly statistically significant association. a age, surgery and hormonal were dropped from the model. Finally, one of the main assumptions of the non-parametric Cox proportional hazard model is proportionality upon which the Cox model and log-rank test procedure are based. This assumption is based on the requirement of the hazard ratios being constant over time or that the hazard for one individual is proportional to the hazard for any other individual. This proportionality constancy is independent of time. The test of proportionality showed clearly that the dependent covariate was statistically non-significant as the global test chi 2 was 1.23, df=4 and p=0.873, an indication of the constancy of hazard over time. This result indicated that the model did not violate the proportionality assumption. So, the appropriateness of the use of the model in the analysis was confirmed. Moreover, interaction in the model analysis showed that these interaction terms had no significant effects on the performance of the model. Discussion A range of factors contributes to global and regional differences in cervical cancer incidence and mortality. Determining the drivers of these variations is complicated and there have been no comprehensive studies looking at this to date. However, stage, clinical features and quality of treatment are the most likely accepted explanations for these international differences. 12 Cervical cancer survival mainly depends on early detection and effective treatment modalities. Thus, by examining this survival through the eyes of prevention and control of the disease at diagnosis, one can assess and evaluate potential covariates with the most impact on patient survival. This study focused on cancer stage at diagnosis as the most important potential predictor covariate of survival. The result showed that these patients were relatively old, married, unemployed, illiterate, urban and belonged to non-Arab descent African groups. Cervical cancer, in Sudan, is described as advanced at presentation and grade, aggressive and invasive squamous cell carcinoma and moderately to poorly differentiated cells leading to poor survival. Several previous studies reached the conclusion of the disease as being invasive and advanced at presentation. 12 , 19 - 21 The stage at diagnosis is much related to survival and cancer survival analysis measures this relationship and the effectiveness of the health care system. This study showed clearly that advanced cancer stage presentation at diagnosis had a significantly negative impact on survival outcomes compared to the early stage. This conclusion is in agreement with previous studies in different developed and developing countries. 14 , 16 , 19 , 21 - 24 Cancer survival is measured as a proportion of cancer patients who remained alive after a specific period, usually 5-years. However, this cancer survival measure is fundamentally influenced by stage, age, treatment therapy and if it is preventable and curable. Cervical cancer is preventable and relatively curable if detected at an early stage though most cancer cases are diagnosed at a late-stage in low- and medium-income countries and Sudan as shown in this study. 6 , 25 - 27 Late-stage diagnosis is correlated with low survival rates, as well as complicated treatment, poor prognosis and survival outcome. 28 - 30 This study demonstrated not only that late-stage cancer diagnosis influences survival negatively but, also, how each predictor covariate affects the slope of the survival curve using Cox regression analysis. In a four step elimination process of confounding factors, the results confirmed strongly that stage, chemotherapy and radiotherapy were the most likely predictor covariates of survival times. This result was in agreement with a recent study in Saudia Arabia. 31 Though the late cancer stage at diagnosis has proven to be closely related to poor survival, there are other factors associated with low survival rates such as socio-demographic, cultural, and economic characteristics of the patient, and histopathological features of the tumor. 12 Aside from the impacted survival rate, diagnosis of cervical cancer at an advanced stage has been explained by delays in diagnosis at presentation and initiation of treatment. 12 For cervical cancer, effective control measures are generally available and affordable. This disease can be, to a large extent, prevented by vaccination against HPV infection and by screening and treating pre-cancerous lesions. Other than this, early detection of cervical cancer is imperative to improve treatment outcomes. Assessment of the study conclusion should be interpreted with caution since the study was based on retrospectively routinely collected data from one referral hospital with the largest registration of cancer patients in the country. It does not include all data of cervical cancer patients in the country and is limited by the type of available data. Due to the huge differences in settings, it is prudent not to extrapolate from one experience in developed countries to others in developing countries. Conclusion and recommendations The results of this study suggest that the cervical cancer stage at diagnosis and certain treatments are the most important factors impacting patient prognosis and survival outcome. The evidence presented has shown the complexity of determining what drives most variations in cancer outcomes between nations. It is most likely all steps the cancer patient takes when seeking medical care contribute to some degree to the differences in cervical cancer survival rates. Cancer survival analysis can help in the diagnosis and treatment of cervical cancer and provide important information about where more effort should be directed. Early detection of cancer and vaccination of women against HPV infection provide tremendous opportunities for prevention, early diagnosis, more effective treatment and a higher probability of better survival and outcomes. Government intervention to reduce the suffering of cervical cancer treatment is of vital importance by providing diagnostic and oncological services in all general public hospitals and introduction of oncology units in all state capital’s public hospitals. Early detection of cervical cancer should be the core of a proposed female cancer strategy through providing intensive and comprehensive vaccination, cervical cancer screening, and raising disease awareness among patients. This strategy needs to be closely linked to primary, secondary and tertiary care services. Data availability Underlying data Zenodo: Elgoraish A. and Alnory A. cervical cancer dataset. http://doi.org/10.5281/zenodo.4399441 32 This project contains the following underlying data: - Cervical cancer dataset Extended data Zenodo: Elgoraish A. Cervical cancer form. https://doi.org/10.5281/zenodo.4469654 33 This project contains the following extended data: - checklist.pdf - consent form.pdf Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC-BY 4.0). Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Acknowledgements We are thankful to all people who participated in the study. We thank the medical and statistical staff of Khartoum oncology hospital for their help in collecting personal and clinical data of cancer patients. Ethical approval This study received ethical approval from the Sudan Federal Ministry of Health (number:3-10-2015, dated: 15/12/2015). The health ministry asked the participating hospital to provide the researchers with existing data of cervical cancer patients in accordance with the protection of the patients’ personal information from improper use as required by law. The ethics board provided a waiver of consent for collecting participant’s medical records before follow-up. When participants were called for follow-up, they or their next of kin were informed about the study and oral informed consent was obtained. References 1. Parkin DM, Bray F, Ferlay J, et al. : Cancer in africa 2012. Cancer Epidemiol Biomarkers Prev. 2014. 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Deverakonda A, Gupta N: Diagnosis and Treatment of Cervical Cancer: Research & Reviews. J Nurs Health Sci. 2016; 2 (Suppl 3). 28. Vinh-Hung V, Bourgain C, Vlastos G, et al. : Prognostic value of histopathology and trends in cervical cancer: a SEER population study. BMC cancer. 2007; 7 (Suppl 1): 164. PubMed Abstract | Publisher Full Text | Free Full Text 29. Thomson CS, Forman D: Cancer survival in England and the influence of early diagnosis: what can we learn from recent EUROCARE results? Br J Cancer. 2009; 101 (Suppl 2): S102-S109. PubMed Abstract | Publisher Full Text | Free Full Text 30. Wassie M, Argaw Z, Tsige Y, et al. : Survival status and associated factors of death among cervical cancer patients attending at Tikur Anbesa Specialized Hospital, Addis Ababa, Ethiopia: a retrospective cohort study. BMC cancer. 2019; 19 (Suppl 1): 1221. PubMed Abstract | Publisher Full Text | Free Full Text 31. Anfinan N, Sait K: Indicators of survival and prognostic factors in women treated for cervical cancer at a tertiary care center in Saudi Arabia. Ann Saudi Med. 2020; 40 (Suppl 1): 25-35. PubMed Abstract | Publisher Full Text | Free Full Text 32. Elgoraish A, Alnory A: Cervical cancer dataset [dataset].Zenodo;2020. Publisher Full Text 33. Elgoraish A: Cervical cancer form.Zenodo;2021. Publisher Full Text Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 15 Feb 2021 ADD YOUR COMMENT Comment Author details Author details 1 Epidemiology, Tropical Medicine Research Institute, National Centre for Research, Khartoum, Khartoum, P.O. Box 1304, Sudan 2 Applied Statistics and Demography, Faculty of Economics and Rural Development, University of Gezira, Medani, Gezira, P.O. Box 20, Sudan Amanda Elgoraish Roles: Conceptualization, Formal Analysis, Methodology, Writing – Original Draft Preparation, Writing – Review & Editing Ahmed Alnory Roles: Conceptualization, Supervision, Writing – Review & Editing Competing interests No competing interests were disclosed. Grant information The author(s) declared that no grants were involved in supporting this work. Article Versions (2) version 2 Revised Published: 07 Oct 2022, 10:114 https://doi.org/10.12688/f1000research.43590.2 version 1 Published: 15 Feb 2021, 10:114 https://doi.org/10.12688/f1000research.43590.1 Copyright © 2022 Elgoraish A and Alnory A. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Download Export To Sciwheel Bibtex EndNote ProCite Ref. 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F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.139379.r152671 ) The direct URL for this report is: https://f1000research.com/articles/10-114/v2#referee-response-152671 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 20 Oct 2022 Elvynna Leong , Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, Brunei Ong Sok King , NCD Prevention Unit, Ministry of Health, Commonwealth Drive, Brunei Approved VIEWS 0 https://doi.org/10.5256/f1000research.139379.r152671 No further ... Continue reading READ ALL No further comments to make. Competing Interests: No competing interests were disclosed. Reviewer Expertise: Statistics, Public Health We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Leong E and Sok King O. Reviewer Report For: Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.139379.r152671 ) The direct URL for this report is: https://f1000research.com/articles/10-114/v2#referee-response-152671 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Respond or Comment COMMENT ON THIS REPORT Version 1 VERSION 1 PUBLISHED 15 Feb 2021 Views 0 Cite How to cite this report: Leong E and Sok King O. Reviewer Report For: Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.46657.r147507 ) The direct URL for this report is: https://f1000research.com/articles/10-114/v1#referee-response-147507 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 06 Sep 2022 Elvynna Leong , Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, Brunei Ong Sok King , NCD Prevention Unit, Ministry of Health, Commonwealth Drive, Brunei Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.46657.r147507 This paper is very meaningful, especially for Sudan, as there are currently not many studies published from the Africa region or Sudan on cervical cancer survival. However, there are a few key components that require further clarification or analysis from ... Continue reading READ ALL This paper is very meaningful, especially for Sudan, as there are currently not many studies published from the Africa region or Sudan on cervical cancer survival. However, there are a few key components that require further clarification or analysis from the researchers. Title The researchers aimed to examine predictors associated with cervical cancer stage at diagnosis and its impact on cancer patient prognosis and survival. However, the title of the paper does not state the word “stage”. Methods Data collection and sources The authors stated a study period of 2011-2015 in the study design and follow-up in 2016. What is the earliest year of diagnosis? Were the participants recruited diagnosed during the 2011-2015 period only? Also, please give more details on the follow-up period. How long was the follow-up period? Is it up to December 2016? Statistical analysis The statement “ Statistical methods such as chi 2 , Kaplan-Meier, log-rank test and Cox regression were used to find out most prognostic factors associated with cancer disease ” is not entirely correct. This needs to be revised. Explain why you used chi 2 , Kaplan-Meier, log-rank test and Cox PH regression separately. " Log-rank test for equality ." We suggest adding more detail on ‘equality’. Results Presentation of results needs to be improved, such as Paragraph 1 in Descriptive statistics: removing at in " (SE=0.88, at 95%CI=55.17-85.65) ". Paragraph 1 in Descriptive statistics: rewriting “majority 82.9% ≥45 years old ”. Table 2: It is very important to keep the statistics consistent in tables, such as p-values of the log-rank test should be kept to 3 decimal places. Table 2: We suggest replacing 0.000 with <0.001, which is more commonly used in literature. Table 2: For Treatment, each p-value from the log-rank test is compared with no treatment? Table 2: On mean of survival time, to label months in the table. Regression analysis: " (chi 2 =33.49, df=3, p=0.000) ". Is chi 2 =33.49 or 31.27, as indicated in Table 2? Regression analysis: " The chi 2 was 7.91, df=1 with p=0.004 ( Table 2 ). " p-value is 0.005 (rounded up to 3 d.p). Regression analysis: “ The graph of the two survival functions curves were statistically equivalent of the two groups ”. The p-value of 0.005 did not indicate statistical equivalence. Table 1 There were indications that geographical locations were significantly associated with stage of diagnosis, further discussion on this could be helpful. For the survival analysis, was there a breakdown by 1-year or 3-years and 5-years survival rates? Was there any comparison or benchmarking of the findings or survival rates with other similar studies? It would also help to have some discussion on the potential explanations for these findings and to suggest for further studies. The researchers could identify the limitations of the study e.g. duration of treatment or any delay in treatment was not analyzed in the study. Some grammar problems should also be paid attention. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Statistics, Public Health We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Leong E and Sok King O. Reviewer Report For: Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.46657.r147507 ) The direct URL for this report is: https://f1000research.com/articles/10-114/v1#referee-response-147507 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 07 Oct 2022 Amanda Elgoraish , Epidemiology, Tropical Medicine Research Institute, National Centre for Research, Khartoum, P.O. Box 1304, Sudan 07 Oct 2022 Author Response Some of your comments and suggestions have been taken care of in the text while others are clarified as below: The study period is called 5-years survival, 2011-2015, starting from ... Continue reading Some of your comments and suggestions have been taken care of in the text while others are clarified as below: The study period is called 5-years survival, 2011-2015, starting from 1 st Jan 2011 till 31 st Dec 2015. The follow-up was passively collected from participants' medical records and active follow-up during the year 2016 by contacting lost-to-follow-up participants to confirm their life status (dead or alive). The log-rank test for equality was intended to compare between different groups of covariates and to confirm their statistical significance differences. The survival tools of analysis were used to explain data analysis to suit descriptive and analytical sections and meet the requirement of each tool of analysis. Table 2: all p-values of the log rank test are kept to 3 decimal places. Table 2: for treatment each p-value of the log rank test basically is treatment and no treatment. Table 1: the location result (east and west) included p-values which were insignificant in the univariate model, but significant in multivariate model. It was also insignificant in the final regression model. The study was intended to examine cases in a referral hospital in Khartoum State. So it is difficult to make final conclusion on a very small dataset of participants outside Khartoum State which was beyond the scope of the study objectives. The study focused on 5-years survival (standard period for cancer survival analysis) and comparison with other short periods was not within the scope of the study. The study discussed other explanations for survival of cervical cancer patients in developing countries despite the paucity of similar studies. It refers to most recent published studies. Delay was mentioned as one of the most plausible explanations for cervical cancer patients' stage at diagnosis. We are in the final stage of presenting our new article on associated predictor covariates at diagnosis focusing on the delay as the most important factor. The study explained clearly its limitation based on availability and quality of data collected from participants' medical files and other sources. Some of your comments and suggestions have been taken care of in the text while others are clarified as below: The study period is called 5-years survival, 2011-2015, starting from 1 st Jan 2011 till 31 st Dec 2015. The follow-up was passively collected from participants' medical records and active follow-up during the year 2016 by contacting lost-to-follow-up participants to confirm their life status (dead or alive). The log-rank test for equality was intended to compare between different groups of covariates and to confirm their statistical significance differences. The survival tools of analysis were used to explain data analysis to suit descriptive and analytical sections and meet the requirement of each tool of analysis. Table 2: all p-values of the log rank test are kept to 3 decimal places. Table 2: for treatment each p-value of the log rank test basically is treatment and no treatment. Table 1: the location result (east and west) included p-values which were insignificant in the univariate model, but significant in multivariate model. It was also insignificant in the final regression model. The study was intended to examine cases in a referral hospital in Khartoum State. So it is difficult to make final conclusion on a very small dataset of participants outside Khartoum State which was beyond the scope of the study objectives. The study focused on 5-years survival (standard period for cancer survival analysis) and comparison with other short periods was not within the scope of the study. The study discussed other explanations for survival of cervical cancer patients in developing countries despite the paucity of similar studies. It refers to most recent published studies. Delay was mentioned as one of the most plausible explanations for cervical cancer patients' stage at diagnosis. We are in the final stage of presenting our new article on associated predictor covariates at diagnosis focusing on the delay as the most important factor. The study explained clearly its limitation based on availability and quality of data collected from participants' medical files and other sources. Competing Interests: No competing interests were disclosed. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 07 Oct 2022 Amanda Elgoraish , Epidemiology, Tropical Medicine Research Institute, National Centre for Research, Khartoum, P.O. Box 1304, Sudan 07 Oct 2022 Author Response Some of your comments and suggestions have been taken care of in the text while others are clarified as below: The study period is called 5-years survival, 2011-2015, starting from ... Continue reading Some of your comments and suggestions have been taken care of in the text while others are clarified as below: The study period is called 5-years survival, 2011-2015, starting from 1 st Jan 2011 till 31 st Dec 2015. The follow-up was passively collected from participants' medical records and active follow-up during the year 2016 by contacting lost-to-follow-up participants to confirm their life status (dead or alive). The log-rank test for equality was intended to compare between different groups of covariates and to confirm their statistical significance differences. The survival tools of analysis were used to explain data analysis to suit descriptive and analytical sections and meet the requirement of each tool of analysis. Table 2: all p-values of the log rank test are kept to 3 decimal places. Table 2: for treatment each p-value of the log rank test basically is treatment and no treatment. Table 1: the location result (east and west) included p-values which were insignificant in the univariate model, but significant in multivariate model. It was also insignificant in the final regression model. The study was intended to examine cases in a referral hospital in Khartoum State. So it is difficult to make final conclusion on a very small dataset of participants outside Khartoum State which was beyond the scope of the study objectives. The study focused on 5-years survival (standard period for cancer survival analysis) and comparison with other short periods was not within the scope of the study. The study discussed other explanations for survival of cervical cancer patients in developing countries despite the paucity of similar studies. It refers to most recent published studies. Delay was mentioned as one of the most plausible explanations for cervical cancer patients' stage at diagnosis. We are in the final stage of presenting our new article on associated predictor covariates at diagnosis focusing on the delay as the most important factor. The study explained clearly its limitation based on availability and quality of data collected from participants' medical files and other sources. Some of your comments and suggestions have been taken care of in the text while others are clarified as below: The study period is called 5-years survival, 2011-2015, starting from 1 st Jan 2011 till 31 st Dec 2015. The follow-up was passively collected from participants' medical records and active follow-up during the year 2016 by contacting lost-to-follow-up participants to confirm their life status (dead or alive). The log-rank test for equality was intended to compare between different groups of covariates and to confirm their statistical significance differences. The survival tools of analysis were used to explain data analysis to suit descriptive and analytical sections and meet the requirement of each tool of analysis. Table 2: all p-values of the log rank test are kept to 3 decimal places. Table 2: for treatment each p-value of the log rank test basically is treatment and no treatment. Table 1: the location result (east and west) included p-values which were insignificant in the univariate model, but significant in multivariate model. It was also insignificant in the final regression model. The study was intended to examine cases in a referral hospital in Khartoum State. So it is difficult to make final conclusion on a very small dataset of participants outside Khartoum State which was beyond the scope of the study objectives. The study focused on 5-years survival (standard period for cancer survival analysis) and comparison with other short periods was not within the scope of the study. The study discussed other explanations for survival of cervical cancer patients in developing countries despite the paucity of similar studies. It refers to most recent published studies. Delay was mentioned as one of the most plausible explanations for cervical cancer patients' stage at diagnosis. We are in the final stage of presenting our new article on associated predictor covariates at diagnosis focusing on the delay as the most important factor. The study explained clearly its limitation based on availability and quality of data collected from participants' medical files and other sources. Competing Interests: No competing interests were disclosed. Close Report a concern COMMENT ON THIS REPORT Views 0 Cite How to cite this report: Hammad N. Reviewer Report For: Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.46657.r84246 ) The direct URL for this report is: https://f1000research.com/articles/10-114/v1#referee-response-84246 NOTE: it is important to ensure the information in square brackets after the title is included in this citation. Close Copy Citation Details Reviewer Report 24 May 2021 Nazik Hammad , Department of Oncology, Queen's University, Kingston, ON, Canada Approved VIEWS 0 https://doi.org/10.5256/f1000research.46657.r84246 Overall, the work is presented well. Some minor details that could be addressed: The introduction is too long and has number of repetitions. It needs to be shortened and made succinct. I recommend replacing ... Continue reading READ ALL Overall, the work is presented well. Some minor details that could be addressed: The introduction is too long and has number of repetitions. It needs to be shortened and made succinct. I recommend replacing developing and developed countries with the more current terms: low-and-middle-income countries ( LMIC ) and high-income countries (HIC). It is best to situate this article in the context of the WHO cervical cancer elimination strategy launched 2020; the 90-70-90 targets for 2030 especially in the recommendation section where Sudan should strive to achieve the WHO cervical cancer elimination targets by 2030. These are measurable targets for the Ministry of Health in Sudan and various stakeholders. The last sentence in the discussion about the prudence of “not extrapolating from one experience in developed countries”, while correct, does not have relevance to the paragraph. I would suggest removing it. The study design is appropriate. Outcome research is desperately needed in LMIC to inform policy and measure that need to be taken to improve access to cancer care across the continuum. I have reviewed the methodology, the consent form and the follow-up and they have sufficient details. However, it would be of added benefit if the following could be addressed: Is there a different intake form that has the employment status and other sociodemographic variables? The authors may wish to explain what is the category “other tribes” that are neither non Arab descent Africans or Arab descent Africans mean. This constitutes 11% of the cohort. It would add to the value of the research if a sentence can be added about how consent was obtained from women who cannot read and write? The statistical analysis is very well done; however, I have the following questions: Has the chemotherapy and radiotherapy use been defined by stage? e.g., how many patients with advanced stage received chemotherapy versus those with early stage? The data shows that 57% of patients received chemotherapy. Was there any correlation between receiving chemotherapy and residing in Khartoum versus peripheral areas, between receiving chemotherapy and education or ethnic origin? The data supports that access to early diagnosis and treatment is needed to improve survival. As such the conclusion is supported by the results. While this is not surprising, it is important for future planning of health services to document this in Sudan. The authors’ use of employment data as an indicator of socioeconomic status (SE) should be listed as a limitation as not all unemployed women in Sudan are of similar SE status especially in this cohort of older women. Household income and area of residence are likely to be indicative of socioeconomic status which may influence access to care. This data might have been difficult to collect but this should also be acknowledged. The data does not provide indications as to the reasons for lack of access to chemotherapy. Lack of treatment details such as completion of a full course or radiotherapy and chemotherapy is also a limitation. Health equity and cancer disparities should be highlighted. The data revealed that these patients are 62.2% non Arab descent African. Is this reflective of the general population in the area or is there more prevalence of cervical cancer among non Arab descent Africans? This is of relevance when planning prevention (vaccination), screening, treatment interventions by targeting the most vulnerable population. The conclusion could be strengthened by calling further research looking into barriers to access to treatment. For example, this current cohort could be further interrogated in the future by investigating details of initiation and completion of treatment including chemotherapy and radiotherapy Overall excellent effort in a much needed area of health services research. I believe the paper has academic merit, but I ask for a number of small changes to the article and response to some queries. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests: No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Hammad N. Reviewer Report For: Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.46657.r84246 ) The direct URL for this report is: https://f1000research.com/articles/10-114/v1#referee-response-84246 NOTE: it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS Report a concern Author Response 30 Jun 2021 Amanda Elgoraish , Epidemiology, Tropical Medicine Research Institute, National Centre for Research, Khartoum, P.O. Box 1304, Sudan 30 Jun 2021 Author Response Your comments concerning length of introduction, using LIMC instead of developing and developed countries and the last sentence of limitation paragraph have been taken notice of and appreciated. The ... Continue reading Your comments concerning length of introduction, using LIMC instead of developing and developed countries and the last sentence of limitation paragraph have been taken notice of and appreciated. The suggestion of outcome research is commended but it is beyond the purpose of this study. However, implementation research is more urgent to assess efficacy and effectiveness of intervention and early detection programmes. Consent and follow-up was conducted by phone to collect vital status data (dead or alive) after explaining purpose of the interview and having verbal consent. Missing socio-demographic data were also, obtained during the interview to complete already collected data from patients medical files and diagnosis profiles. Other tribes indicate to participants who were Sudanese but did not belong to any of the known Sudanese tribes. They are most likely belong to non-Sudanese foreign ethnic groups. Participant were classified as early or advanced stages at diagnosis and majority of them were at the advanced stage. Thus, most of participants who received chemo and radio therapies are most likely belong to this advanced stage. The study focus was on stage at diagnosis as the major determinant of survival. Other socio-demographic factors, residence state and rural/urban centres were considered insignificant confounding variables. Household income and area of residence are proxy of socio-economic status and may influence access to care but the final conclusion of data analysis after removal of confounding variables and interaction terms affirmed that only stage at diagnosis and chemo and radio therapies are the effectors of cervical patient survival and outcome. The majority of participants of cervical cancer disease were from the non-Arab decent African tribes is an indication which can be of great help in planning vaccination and screening programmes. Suggested future research on barriers to treatment is commended but barriers to early detection is more urgent and appropriate in the short term future perspective. Sufficient details of methods and analysis and source data are available and adequate for further reproducibility by looking into data availability section of the article. Amanda Elgoraish Corresponding author Your comments concerning length of introduction, using LIMC instead of developing and developed countries and the last sentence of limitation paragraph have been taken notice of and appreciated. The suggestion of outcome research is commended but it is beyond the purpose of this study. However, implementation research is more urgent to assess efficacy and effectiveness of intervention and early detection programmes. Consent and follow-up was conducted by phone to collect vital status data (dead or alive) after explaining purpose of the interview and having verbal consent. Missing socio-demographic data were also, obtained during the interview to complete already collected data from patients medical files and diagnosis profiles. Other tribes indicate to participants who were Sudanese but did not belong to any of the known Sudanese tribes. They are most likely belong to non-Sudanese foreign ethnic groups. Participant were classified as early or advanced stages at diagnosis and majority of them were at the advanced stage. Thus, most of participants who received chemo and radio therapies are most likely belong to this advanced stage. The study focus was on stage at diagnosis as the major determinant of survival. Other socio-demographic factors, residence state and rural/urban centres were considered insignificant confounding variables. Household income and area of residence are proxy of socio-economic status and may influence access to care but the final conclusion of data analysis after removal of confounding variables and interaction terms affirmed that only stage at diagnosis and chemo and radio therapies are the effectors of cervical patient survival and outcome. The majority of participants of cervical cancer disease were from the non-Arab decent African tribes is an indication which can be of great help in planning vaccination and screening programmes. Suggested future research on barriers to treatment is commended but barriers to early detection is more urgent and appropriate in the short term future perspective. Sufficient details of methods and analysis and source data are available and adequate for further reproducibility by looking into data availability section of the article. Amanda Elgoraish Corresponding author Competing Interests: I have no competing interests Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 30 Jun 2021 Amanda Elgoraish , Epidemiology, Tropical Medicine Research Institute, National Centre for Research, Khartoum, P.O. Box 1304, Sudan 30 Jun 2021 Author Response Your comments concerning length of introduction, using LIMC instead of developing and developed countries and the last sentence of limitation paragraph have been taken notice of and appreciated. The ... Continue reading Your comments concerning length of introduction, using LIMC instead of developing and developed countries and the last sentence of limitation paragraph have been taken notice of and appreciated. The suggestion of outcome research is commended but it is beyond the purpose of this study. However, implementation research is more urgent to assess efficacy and effectiveness of intervention and early detection programmes. Consent and follow-up was conducted by phone to collect vital status data (dead or alive) after explaining purpose of the interview and having verbal consent. Missing socio-demographic data were also, obtained during the interview to complete already collected data from patients medical files and diagnosis profiles. Other tribes indicate to participants who were Sudanese but did not belong to any of the known Sudanese tribes. They are most likely belong to non-Sudanese foreign ethnic groups. Participant were classified as early or advanced stages at diagnosis and majority of them were at the advanced stage. Thus, most of participants who received chemo and radio therapies are most likely belong to this advanced stage. The study focus was on stage at diagnosis as the major determinant of survival. Other socio-demographic factors, residence state and rural/urban centres were considered insignificant confounding variables. Household income and area of residence are proxy of socio-economic status and may influence access to care but the final conclusion of data analysis after removal of confounding variables and interaction terms affirmed that only stage at diagnosis and chemo and radio therapies are the effectors of cervical patient survival and outcome. The majority of participants of cervical cancer disease were from the non-Arab decent African tribes is an indication which can be of great help in planning vaccination and screening programmes. Suggested future research on barriers to treatment is commended but barriers to early detection is more urgent and appropriate in the short term future perspective. Sufficient details of methods and analysis and source data are available and adequate for further reproducibility by looking into data availability section of the article. Amanda Elgoraish Corresponding author Your comments concerning length of introduction, using LIMC instead of developing and developed countries and the last sentence of limitation paragraph have been taken notice of and appreciated. The suggestion of outcome research is commended but it is beyond the purpose of this study. However, implementation research is more urgent to assess efficacy and effectiveness of intervention and early detection programmes. Consent and follow-up was conducted by phone to collect vital status data (dead or alive) after explaining purpose of the interview and having verbal consent. Missing socio-demographic data were also, obtained during the interview to complete already collected data from patients medical files and diagnosis profiles. Other tribes indicate to participants who were Sudanese but did not belong to any of the known Sudanese tribes. They are most likely belong to non-Sudanese foreign ethnic groups. Participant were classified as early or advanced stages at diagnosis and majority of them were at the advanced stage. Thus, most of participants who received chemo and radio therapies are most likely belong to this advanced stage. The study focus was on stage at diagnosis as the major determinant of survival. Other socio-demographic factors, residence state and rural/urban centres were considered insignificant confounding variables. Household income and area of residence are proxy of socio-economic status and may influence access to care but the final conclusion of data analysis after removal of confounding variables and interaction terms affirmed that only stage at diagnosis and chemo and radio therapies are the effectors of cervical patient survival and outcome. The majority of participants of cervical cancer disease were from the non-Arab decent African tribes is an indication which can be of great help in planning vaccination and screening programmes. Suggested future research on barriers to treatment is commended but barriers to early detection is more urgent and appropriate in the short term future perspective. Sufficient details of methods and analysis and source data are available and adequate for further reproducibility by looking into data availability section of the article. Amanda Elgoraish Corresponding author Competing Interests: I have no competing interests Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 15 Feb 2021 ADD YOUR COMMENT Comment keyboard_arrow_left keyboard_arrow_right Open Peer Review Reviewer Status info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Reviewer Reports Invited Reviewers 1 2 Version 2 (revision) 07 Oct 22 read Version 1 15 Feb 21 read read Nazik Hammad , Queen's University, Kingston, Canada Elvynna Leong , Universiti Brunei Darussalam, Jalan Tungku Link, Brunei Ong Sok King , Ministry of Health, Commonwealth Drive, Brunei Comments on this article All Comments (0) Add a comment Sign up for content alerts Sign Up You are now signed up to receive this alert Browse by related subjects keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2022 Leong E et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 20 Oct 2022 | for Version 2 Elvynna Leong , Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, Brunei Ong Sok King , NCD Prevention Unit, Ministry of Health, Commonwealth Drive, Brunei 0 Views copyright © 2022 Leong E et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (0) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions No further comments to make. Competing Interests No competing interests were disclosed. Reviewer Expertise Statistics, Public Health We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (0) Leong E and Sok King O. Peer Review Report For: Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.139379.r152671) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/10-114/v2#referee-response-152671 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2022 Leong E et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 06 Sep 2022 | for Version 1 Elvynna Leong , Faculty of Science, Universiti Brunei Darussalam, Jalan Tungku Link, Brunei Ong Sok King , NCD Prevention Unit, Ministry of Health, Commonwealth Drive, Brunei 0 Views copyright © 2022 Leong E et al. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved With Reservations info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions This paper is very meaningful, especially for Sudan, as there are currently not many studies published from the Africa region or Sudan on cervical cancer survival. However, there are a few key components that require further clarification or analysis from the researchers. Title The researchers aimed to examine predictors associated with cervical cancer stage at diagnosis and its impact on cancer patient prognosis and survival. However, the title of the paper does not state the word “stage”. Methods Data collection and sources The authors stated a study period of 2011-2015 in the study design and follow-up in 2016. What is the earliest year of diagnosis? Were the participants recruited diagnosed during the 2011-2015 period only? Also, please give more details on the follow-up period. How long was the follow-up period? Is it up to December 2016? Statistical analysis The statement “ Statistical methods such as chi 2 , Kaplan-Meier, log-rank test and Cox regression were used to find out most prognostic factors associated with cancer disease ” is not entirely correct. This needs to be revised. Explain why you used chi 2 , Kaplan-Meier, log-rank test and Cox PH regression separately. " Log-rank test for equality ." We suggest adding more detail on ‘equality’. Results Presentation of results needs to be improved, such as Paragraph 1 in Descriptive statistics: removing at in " (SE=0.88, at 95%CI=55.17-85.65) ". Paragraph 1 in Descriptive statistics: rewriting “majority 82.9% ≥45 years old ”. Table 2: It is very important to keep the statistics consistent in tables, such as p-values of the log-rank test should be kept to 3 decimal places. Table 2: We suggest replacing 0.000 with <0.001, which is more commonly used in literature. Table 2: For Treatment, each p-value from the log-rank test is compared with no treatment? Table 2: On mean of survival time, to label months in the table. Regression analysis: " (chi 2 =33.49, df=3, p=0.000) ". Is chi 2 =33.49 or 31.27, as indicated in Table 2? Regression analysis: " The chi 2 was 7.91, df=1 with p=0.004 ( Table 2 ). " p-value is 0.005 (rounded up to 3 d.p). Regression analysis: “ The graph of the two survival functions curves were statistically equivalent of the two groups ”. The p-value of 0.005 did not indicate statistical equivalence. Table 1 There were indications that geographical locations were significantly associated with stage of diagnosis, further discussion on this could be helpful. For the survival analysis, was there a breakdown by 1-year or 3-years and 5-years survival rates? Was there any comparison or benchmarking of the findings or survival rates with other similar studies? It would also help to have some discussion on the potential explanations for these findings and to suggest for further studies. The researchers could identify the limitations of the study e.g. duration of treatment or any delay in treatment was not analyzed in the study. Some grammar problems should also be paid attention. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Partly Are all the source data underlying the results available to ensure full reproducibility? Yes Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Statistics, Public Health We confirm that we have read this submission and believe that we have an appropriate level of expertise to confirm that it is of an acceptable scientific standard, however we have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 07 Oct 2022 Amanda Elgoraish, Epidemiology, Tropical Medicine Research Institute, National Centre for Research, Khartoum, P.O. Box 1304, Sudan Some of your comments and suggestions have been taken care of in the text while others are clarified as below: The study period is called 5-years survival, 2011-2015, starting from 1 st Jan 2011 till 31 st Dec 2015. The follow-up was passively collected from participants' medical records and active follow-up during the year 2016 by contacting lost-to-follow-up participants to confirm their life status (dead or alive). The log-rank test for equality was intended to compare between different groups of covariates and to confirm their statistical significance differences. The survival tools of analysis were used to explain data analysis to suit descriptive and analytical sections and meet the requirement of each tool of analysis. Table 2: all p-values of the log rank test are kept to 3 decimal places. Table 2: for treatment each p-value of the log rank test basically is treatment and no treatment. Table 1: the location result (east and west) included p-values which were insignificant in the univariate model, but significant in multivariate model. It was also insignificant in the final regression model. The study was intended to examine cases in a referral hospital in Khartoum State. So it is difficult to make final conclusion on a very small dataset of participants outside Khartoum State which was beyond the scope of the study objectives. The study focused on 5-years survival (standard period for cancer survival analysis) and comparison with other short periods was not within the scope of the study. The study discussed other explanations for survival of cervical cancer patients in developing countries despite the paucity of similar studies. It refers to most recent published studies. Delay was mentioned as one of the most plausible explanations for cervical cancer patients' stage at diagnosis. We are in the final stage of presenting our new article on associated predictor covariates at diagnosis focusing on the delay as the most important factor. The study explained clearly its limitation based on availability and quality of data collected from participants' medical files and other sources. View more View less Competing Interests No competing interests were disclosed. reply Respond Report a concern Leong E and Sok King O. Peer Review Report For: Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.46657.r147507) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/10-114/v1#referee-response-147507 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2021 Hammad N. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. 24 May 2021 | for Version 1 Nazik Hammad , Department of Oncology, Queen's University, Kingston, ON, Canada 0 Views copyright © 2021 Hammad N. This is an open access peer review report distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. format_quote Cite this report speaker_notes Responses (1) Approved info_outline Alongside their report, reviewers assign a status to the article: Approved The paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. Not approved Fundamental flaws in the paper seriously undermine the findings and conclusions Overall, the work is presented well. Some minor details that could be addressed: The introduction is too long and has number of repetitions. It needs to be shortened and made succinct. I recommend replacing developing and developed countries with the more current terms: low-and-middle-income countries ( LMIC ) and high-income countries (HIC). It is best to situate this article in the context of the WHO cervical cancer elimination strategy launched 2020; the 90-70-90 targets for 2030 especially in the recommendation section where Sudan should strive to achieve the WHO cervical cancer elimination targets by 2030. These are measurable targets for the Ministry of Health in Sudan and various stakeholders. The last sentence in the discussion about the prudence of “not extrapolating from one experience in developed countries”, while correct, does not have relevance to the paragraph. I would suggest removing it. The study design is appropriate. Outcome research is desperately needed in LMIC to inform policy and measure that need to be taken to improve access to cancer care across the continuum. I have reviewed the methodology, the consent form and the follow-up and they have sufficient details. However, it would be of added benefit if the following could be addressed: Is there a different intake form that has the employment status and other sociodemographic variables? The authors may wish to explain what is the category “other tribes” that are neither non Arab descent Africans or Arab descent Africans mean. This constitutes 11% of the cohort. It would add to the value of the research if a sentence can be added about how consent was obtained from women who cannot read and write? The statistical analysis is very well done; however, I have the following questions: Has the chemotherapy and radiotherapy use been defined by stage? e.g., how many patients with advanced stage received chemotherapy versus those with early stage? The data shows that 57% of patients received chemotherapy. Was there any correlation between receiving chemotherapy and residing in Khartoum versus peripheral areas, between receiving chemotherapy and education or ethnic origin? The data supports that access to early diagnosis and treatment is needed to improve survival. As such the conclusion is supported by the results. While this is not surprising, it is important for future planning of health services to document this in Sudan. The authors’ use of employment data as an indicator of socioeconomic status (SE) should be listed as a limitation as not all unemployed women in Sudan are of similar SE status especially in this cohort of older women. Household income and area of residence are likely to be indicative of socioeconomic status which may influence access to care. This data might have been difficult to collect but this should also be acknowledged. The data does not provide indications as to the reasons for lack of access to chemotherapy. Lack of treatment details such as completion of a full course or radiotherapy and chemotherapy is also a limitation. Health equity and cancer disparities should be highlighted. The data revealed that these patients are 62.2% non Arab descent African. Is this reflective of the general population in the area or is there more prevalence of cervical cancer among non Arab descent Africans? This is of relevance when planning prevention (vaccination), screening, treatment interventions by targeting the most vulnerable population. The conclusion could be strengthened by calling further research looking into barriers to access to treatment. For example, this current cohort could be further interrogated in the future by investigating details of initiation and completion of treatment including chemotherapy and radiotherapy Overall excellent effort in a much needed area of health services research. I believe the paper has academic merit, but I ask for a number of small changes to the article and response to some queries. Is the work clearly and accurately presented and does it cite the current literature? Yes Is the study design appropriate and is the work technically sound? Yes Are sufficient details of methods and analysis provided to allow replication by others? Partly If applicable, is the statistical analysis and its interpretation appropriate? Yes Are all the source data underlying the results available to ensure full reproducibility? Partly Are the conclusions drawn adequately supported by the results? Yes Competing Interests No competing interests were disclosed. I confirm that I have read this submission and believe that I have an appropriate level of expertise to confirm that it is of an acceptable scientific standard. reply Respond to this report Responses (1) Author Response 30 Jun 2021 Amanda Elgoraish, Epidemiology, Tropical Medicine Research Institute, National Centre for Research, Khartoum, P.O. Box 1304, Sudan Your comments concerning length of introduction, using LIMC instead of developing and developed countries and the last sentence of limitation paragraph have been taken notice of and appreciated. The suggestion of outcome research is commended but it is beyond the purpose of this study. However, implementation research is more urgent to assess efficacy and effectiveness of intervention and early detection programmes. Consent and follow-up was conducted by phone to collect vital status data (dead or alive) after explaining purpose of the interview and having verbal consent. Missing socio-demographic data were also, obtained during the interview to complete already collected data from patients medical files and diagnosis profiles. Other tribes indicate to participants who were Sudanese but did not belong to any of the known Sudanese tribes. They are most likely belong to non-Sudanese foreign ethnic groups. Participant were classified as early or advanced stages at diagnosis and majority of them were at the advanced stage. Thus, most of participants who received chemo and radio therapies are most likely belong to this advanced stage. The study focus was on stage at diagnosis as the major determinant of survival. Other socio-demographic factors, residence state and rural/urban centres were considered insignificant confounding variables. Household income and area of residence are proxy of socio-economic status and may influence access to care but the final conclusion of data analysis after removal of confounding variables and interaction terms affirmed that only stage at diagnosis and chemo and radio therapies are the effectors of cervical patient survival and outcome. The majority of participants of cervical cancer disease were from the non-Arab decent African tribes is an indication which can be of great help in planning vaccination and screening programmes. Suggested future research on barriers to treatment is commended but barriers to early detection is more urgent and appropriate in the short term future perspective. Sufficient details of methods and analysis and source data are available and adequate for further reproducibility by looking into data availability section of the article. Amanda Elgoraish Corresponding author View more View less Competing Interests I have no competing interests reply Respond Report a concern Hammad N. Peer Review Report For: Associated predictor covariates of cervical cancer stage and impact on survival at Khartoum oncology hospital, Sudan [version 2; peer review: 2 approved] . F1000Research 2022, 10 :114 ( https://doi.org/10.5256/f1000research.46657.r84246) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. The direct URL for this report is: https://f1000research.com/articles/10-114/v1#referee-response-84246 Alongside their report, reviewers assign a status to the article: Approved - the paper is scientifically sound in its current form and only minor, if any, improvements are suggested Approved with reservations - A number of small changes, sometimes more significant revisions are required to address specific details and improve the papers academic merit. 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