High-risk HPV genotypes in Zimbabwean women with cervical cancer: Comparative analyses between HIV-negative and HIV-positive women

Oppah Kuguyo; Racheal S. Dube Mandishora; Nicholas Ekow Thomford; Rudo Makunike-Mutasa; Charles F. B. Nhachi; Alice Matimba; Collet Dandara

doi:10.1371/journal.pone.0257324

Peer Review History

Original SubmissionFebruary 5, 2021
19 Mar 2021 Decision Letter - Joakim Dillner, Editor PONE-D-21-04071 High-Risk HPV genotypes in Zimbabwean women with cervical cancer: Comparative Analyses between HIV-negative and HIV-positive women. PLOS ONE Dear Dr. Dandara, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Please submit your revised manuscript by Apr 26 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. 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Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: Yes Reviewer #2: Yes ****** 5. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: This cross-sectional study on HPV types in 258 cases of cervical cancer in Zimbabwe, categorized by HIV status, supports earlier results, which have shown that differences in HPV type distribution diminishes with the severity of the cervical lesions. This study also brings more data to the growing body of knowledge regarding the increased proportion of HPV35 in women from sub-Saharan Africa/ancestry. 1. Throughout the text “despite” is often used when it should be “irrespective of” or “regardless of” for example third line in result-section of abstract. 2. Methods: I would suggest using regression analyses for Table 2, 3 and 4 rather than Chi2. Either Poisson regression for prevalence ratios or Logistic regression for odds ratios. 3. Results: I suggest categorizing by HIV status in Figure 2. 4. Results: For better understanding of Figure 3A and Figure 3B it might be better if the absolute numbers of certain genotype combinations were presented. I lack an explanation as to how to assess the odds ratios (eg OR increased at 3.3 for the most common combination 16/35 but decreased at OR 0.3 for the second most common combination 16/18. Is 16 reference?). 5. Results: It says 58% having 2 HR-HPVs in the text but 59% in Table 3. 6. Supplementary Table 1. Suggest adding HIV as risk factor Reviewer #2: In this hospital-based cross-sectional study, the authors examine the distribution of high-risk HPV in HIV+ and HIV- women in Zimbabwe. The study reported high prevalent of HPV 35 among women confirmed with cervical cancer, and HIV status was not associated with frequency, multiplicity and consanguinity of HR-HPV in cervical cancer. The study is well-designed and performed, and also provides important information on high-risk HPV distribution in African women. Several aspects could be further clarified: 1. It would be informative to provide a brief description of the HPV vaccination program and uptake in Zimbabwe early in the introduction. 2. Could the authors clarify the reasons of only including cervical cancer diagnosed at stage 1b-4. 3. It seems the histopathological characteristics are available for all cases included in this study. Such information should be included in the descriptive analysis. 4. Maybe only relevant covariables to the current study are needed to be described. Some of the information collected through the project but not used for the study might not be necessary to mention, such as weight, height, comorbidities and treatment etc. 5. I figure no significant association was detected in the univariate regression between HPV-related risk factors (i.e., age, sexual debut, parity and STI history) and any HR-HPV genotypes might be due to limited power, when the HR-HPV types were stratified by each type. However, those are known factors that associated with HPV infection. Could the authors provide estimates (figure 3b) additionally adjusting for those factors and histology at least as sensitivity analysis when examine the co-occurrence of HPV types. Besides, please clarify what is the reference group for the ORs. 6. A legend explaining how the HR-HPV types were classified (ie. hierarchical classification) especially for those cases with multiple types of HPV infection in table 1 could be informative. 7. In table 4, could the authors clarify the data source for the HPV types in each region of Africa if they are from external studies? 8. Could the authors provide a detailed descriptive table as supplement the distribution of HR-HPV types by HIV status for all included women (including the specific types for multiple infections)? ****** 6. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. 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Revision 1
10 May 2021 Author Response Response to reviewer comments: PONE-D-21-04071 28 April 2021 Dear Professor, Joakim Dilner, Thank you for reviewing our manuscript PONE-D-21-04071- entitled “High-Risk HPV genotypes in Zimbabwean women with cervical cancer: Comparative Analyses between HIV-negative and HIV-positive women” and providing us with constructive criticism on how to improve the statistical analysis and the scientific soundness of the work. Below are our responses to each of the reviewers’ and editor’s comments. Reviewer #1: 1. Throughout the text “despite” is often used when it should be “irrespective of” or “regardless of” for example third line in result-section of abstract Thank you for pointing this out. The authors have edited the document accordingly, and replaced the word “despite” with other terminologies 2. Methods: I would suggest using regression analyses for Table 2, 3 and 4 rather than Chi2. Either Poisson regression for prevalence ratios or Logistic regression for odds ratios. Thank you for this suggestion. The re-analysis for Tables 2 and 3 was performed, as per the reviewer’s recommendations. Data generated for Table 2 was tested using Poisson’s regression, while Table 3 was analysed using logistic regression. However, Table 4 compares absolute frequencies for the HPV genotypes as recorded by an established database, the HPV Information Centre (https://hpvcentre.net) and so the best analyses to compare these frequencies is using the Chi2 statistical methods. Table 2: HR-HPV genotypes by HIV status (n=258) and the HPV phylogenetic classification. Frequency (Proportion) HPV genotype All HIV negative HIV positive IRR (95% CI) p value Negative 10 (0.04) 6 (0.02) 4 (0.02) 0.40 (0.22 – 1.00) 0.443 16a 123 (0.48) 66 (0.26) 57 (0.22) 0.97 (0.69 - 1.37) 0.881 18b 65 (0.25) 34 (0.13) 31 (0.12) 1.11 (0.78 – 1.57) 0.573 31a 17 (0.07) 8 (0.03) 9 (0.04) 1.06 (0.57 – 1.96) 0.854 33a 25 (0.10) 18 (0.07) 7 (0.03) 0.81 (0.49 – 1.34) 0.416 35a 68 (0.26) 40 (0.16) 28 (0.10) 0.90 (0.63 – 1.29) 0.574 39b 10 (0.04) 3 (0.01) 7 (0.03) 1.42 (0.67 – 3.05) 0.361 45b 14 (0.05) 8 (0.03) 6 (0.02) 1.05 (0.53 – 2.06) 0.892 51c 11 (0.04) 5 (0.02) 6 (0.02) 1.35 (0.75 – 2.45) 0.316 52a 9 (0.04) 5 (0.02) 4 (0.02) 0.88 (0.33 – 2.38) 0.799 56d 6 (0.02) 2 (0.0) 4 (0.02) 1.11 (0.41 – 2.99) 0.843 58a 23 (0.11) 9 (0.05) 14 (0.05) 1.28 (0.78 – 2.09) 0.334 59b 3 (0.01) 0 (0.00) 3 (0.01) 1.67 (0.53 – 5.24) 0.380 66d 1 (0.0) 0 (0.00) 1 (0.01) 1.1 (0.15 – 7.89) 0.922 68b 7 (0.03) 2 (0.01) 5 (0.02) 1.23 (0.51 – 3.01) 0.645 IRR= incidence rate ratio computed from the Poisson regression analysis a= Human papillomavirus alpha 9 species; b= Human papillomavirus alpha 7 species; c= Human papillomavirus alpha 5 species; d= Human papillomavirus alpha 6 species. Table 3: Multiple HR-HPV infections, stratified by HIV status (n=163). Number of HPVs found together Frequency (Proportion) All HIV negative HIV positive OR (95% CI) p-value 2 94 (0.59) 45 (0.28) 50 (0.31) 1.65 (0.46 – 5.98) 0.443 3 31 (0.19) 16 (0.10) 15 (0.09) 2.10 (0.55 –8.01) 0.277 4 19 (0.12) 11 (0.07) 8 (0.05) 0.80 (0.16 – 4.02) 0.782 5 12 (0.08) 6 (0.04) 6 (0.04) 1.75 (0.08- 36.28) 0.718 6 6 (0.04) 4 (0.03) 2 (0.01) 1.2 (0.34 – 4.41) 0.756 3. Results: I suggest categorizing by HIV status in Figure 2. The authors appreciate this recommendation and have presented the data as recommended, please see below. Figure 2: The HPV mono infection distribution in women with confirmed cervical cancer (n=85). 4. Results: For better understanding of Figure 3A and Figure 3B it might be better if the absolute numbers of certain genotype combinations were presented. I lack an explanation as to how to assess the odds ratios (eg OR increased at 3.3 for the most common combination 16/35 but decreased at OR 0.3 for the second most common combination 16/18. Is 16 reference?). Thank you for indicating this, a supplementary table was added to this effect (Supplementary Table 2). Logistic regression analysis was performed to estimate the co-occurrence by adding the two specific HPV genotypes as the predictor and co-variate. For example, where HPV16/18 are analysed, it indicates that HPV16 is the predictor, and HPV18 is the covariate. In the comparative analysis, the reference is the whole dataset, less the HPV genotypes being analysed for co-occurrence. Supplementary Table 2: HPV co-occurrence regression analysis, without HIV status, and with HIV status as a co-variate. Composite Genotypes N (proportion) OR (95% CI)a pa OR (95% CI)b pb 16/18 44 (0.17) 0.3 (0.2- 0.5) <0.001 0.3 (0.2- 0.5) <0.001 16/31 14 (0.05) 0.9 (0.4-2.2) 0.824 1 (0.4- 2.1) 0.773 16/33 18 (0.07) 0.3 (0.2 – 0.6) 0.001 0.3 (0.2-0.7) 0.001 16/35 83 (0.32) 3.3 (1.9 – 5.7) <0.001 3.7 (2.1-6.4) <0.001 16/39 6 (0.02) 0.7 (0.2 – 2.3) 0.555 0.6 (0.2 – 2.9) 0.358 16/45 14 (0.05) 1.7 (0.6 – 4.8) 0.325 1.7 (0.6 – 5.0) 0.331 16/51 15 (0.06) 1.8 (0.6 – 5.2) 0.257 1.6 (0.6 – 4.6) 0.386 16/52 5 (0.02) 0.6 (0.2 – 2.0) 0.391 0.6 (0.2 – 2.2) 0.426 16/56 7 (0.03) 4.2 (0.5 – 34.8) 0.181 4.3 (0.5 – 36.1) 0.182 16/58 23 (0.09) 1.4 (0.6 – 3.2) 0.410 1.4 (0.6 – 3.2) 0.410 16/59 1 (0.00) 0.2 (0.0 – 1.9) 0.154 0.1 (0.0 – 1.3) 0.083 18/31 5 (0.02) 0.6 (0.21 – 1.6) 0.285 0.5 (0.2 – 1.5) 0.250 18/33 12 (0.05) 0.7 (0.4 – 1.5) 0.422 0.8 (0.4 – 1.7) 0.567 18/35 26 (0.10) 0.6 (0.4 – 1.0) 0.068 0.6 (0.4 – 1.1) 0.089 18/39 1 (0.00) 0.2 (0.0 – 1.6) 0.135 0.2 (0.0- 1.3) 0.088 18/45 3 (0.01) 0.4 (0.1 – 1.3) 0.134 0.4 (0.1 – 1.3) 0.116 18/51 7 (0.03) 1.2 (0.4 – 3.0) 0.753 1.0 (0.4 – 2.7) 0.998 18/52 3 (0.01) 0.9 (0.2 – 3.6) 0.899 1.0 (0.2 – 4.0) 0.961 18/56 4 (0.02) 2.2 (0.5 – 8.9) 0.275 2.2 (0.5 – 9.3) 0.291 18/58 11 (0.04) 1.1 (0.5 – 2.5) 0.745 1.0 (0.5 – 2.2) 0.979 18/59 2 (0.01) 2.2 (0.3 – 15.6) 0.443 1.7 (0.2 – 12.5) 0.621 18/68 1 (0.00) 0.3 (0.0 – 2.1) 0.207 0.2 (0.0 – 1.8) 0.164 31/33 1 (0.00) 0.3 (0.0 – 2.1) 0.210 0.3 (0.0 – 1.9) 0.183 31/35 7 (0.03) 0.9 (0.3 – 2.2) 0.751 0.9 (0.4 – 2.3) 0.823 31/45 3 (0.01) 0.3 (0.0 - 1.9 ) 0.183 2.5 (0.7 -9.7) 0.169 31/51 2 (0.01) 1.4 (0.3 – 6.6) 0.647 1.2 (0.3 – 5.8) 0.784 31/52 3 (0.01) 6.0 (1.4 – 25.1) 0.014 6.8 (1.6 – 29.2) 0.010 31/56 1 (0.00) 1.8 (0.2 – 15.5) 0.582 1.8 (0.2 – 15.4) 0.608 31/58 1 (0.00) 0.4 (0.0 – 2.9) 0.348 0.3 (0.0 – 2.6) 0.291 31/68 1 (0.00) 1.6 (0.2 – 13.3) 0.668 1.5 (0.2 – 12.4) 0.734 33/35 8 (0.03) 0.4 (1.2 - 0.9) 0.019 0.4 (0.2 -0.9) 0.024 33/39 1(0.00) 0.6 (0.1 – 4.7) 0.610 0.5 (0.1 – 3.9) 0.494 33/45 4 (0.02) 1.6 (0.5 – 5.2) 0.404 1.6 (0.5 – 5.3) 0.418 33/51 2 (0.01) 0.6 (0.1 – 2.9) 0.560 0.5 (0.1 – 2.5) 0.432 33/52 1 (0.00) 0.6 (0.1 – 5.3) 0.685 0.7 (0.0 – 5.6) 0.720 33/58 5 (0.02) 1.1 (0.4 – 3.0) 0.845 1.0 (0.4 – 2.7) 0.977 33/68 3 (0.01) 2.9 (0.7 – 12.6) 0.150 3.1 (0.7 – 12.9) 0.120 35/39 2 (0.01) 0.4 (0.1 – 2.0) 0.288 0.3 (0.1 -1.7) 0.185 35/45 5 (0.02) 0.4 (0.1 – 2.0) 0.288 0.7 (0.2 -2.0) 0.462 35/51 13 (0.05) 4.1 (1.6 – 10.6) 0.004 4.0 (1.4 – 10.0) 0.008 35/52 2 (0.01) 0.5 (0.1 – 2.3) 0.369 0.5 (0.1 – 2.5) 0.394 35/56 3 (0.01) 1.2 (0.3 – 5.1) 0.805 1.1 (0.3 – 5.1) 0.851 35/58 12 (0.05) 1.2 (0.6 – 2.6) 0.608 1.1 (0.5 – 2.4) 0.832 35/66 1 (0.00) 2 (0.1 – 32.3) 0.625 2.0 (0.1 – 35.0) 0.639 39/45 1 (0.00) 1.6 (0.2 – 12.9) 0.677 1.5 (0.2 -12.9) 0.690 39/51 3 (0.01) 6.2 (1.5-25.7) 0.011 5.5 (1.3 – 23.1) 0.019 39/56 2 (0.01) 11 1.9 -62) 0.007 10.9 (2.0 - 64.3) 0.008 39/58 1 (0.00) 0.9 (0.1 -7.0) 0.894 1 (0.1 – 6.3) 0.810 39/59 1 (0.00) 9.9 (0.9 - 103) 0.056 7.8 (0.7 – 84.6) 0.090 39/68 1 (0.00) 3.4 (0.4 – 30.1) 0.279 3.6 (0.5 – 30.0) 0.280 45/52 1 (0.00) 1.9 (0.2 – 15.9) 0.569 1.9 (0.2 – 15.9) 0.569 45/56 1 (0.00) 2.2 (0.2 – 19.3) 0.479 2.2 (0.2 – 19.3) 0.479 45/58 1 (0.00) 0.4 (0.0 – 3.2) 0.400 0.4 (0.0 – 3.2) 0.400 45/59 1 (0.00) 4.2 (0.4 – 43.8) 0.229 4.2 (0.4 – 43.8) 0.229 45/68 1 (0.00) 2.0 (0.2 - 16.6) 0.533 1.8 (0.2 – 15.6) 0.591 51/52 1 (0.00) 1.6 (0.2 – 13.7) 0.643 1.4 (0.2 – 12.0) 0.740 51/56 2 (0.01) 5.3 (1.0 – 28.0) 0.051 5.3 (1.0 – 28.9) 0.056 51/58 2 (0.01) 1.0 (0.2 – 4.4) 0.965 0.9 (0.2 – 3.9) 0.847 58/68 2 (0.01) 2.3 (1.0 – 11.2) 0.300 2.4 (0.5- 12.5) 0.296 59/68 2 (0.01) 42 (5.3 – 349.4) 0.001 35.4 (4.2 - 301) 0.001 66/68 1 (0.00) 37 (2.2 – 565.6) 0.013 40 (2-766.4) 0.014 a- analyses with no consideration of HIV status; b- analyses with HIV status as a co-variate 5. Results: It says 58% having 2 HR-HPVs in the text but 59% in Table 3. Thank you for this observation, this statement has been clarified based on re-analysis of the data, and the actual value is 59%. 6. Supplementary Table 1. Suggest adding HIV as risk factor The authors appreciate this recommendation and have presented the data as recommended. Supplementary Table 1: Risk factors of HPV in association with the various HPV genotypes Odds ratio 95% CI P value HPV16 Age 1.0 0.9 – 1.0 0.686 Sexual debut 0.8 0.6 - 1.2 0.304 Parity 1.7 0.8 – 3.6 0.146 STI history 0.7 0.1 – 7.7 0.751 HIV 1.0 0.6 – 1.5 0.839 HPV18 Age 12.5 -13 – 38 0.333 Sexual debut -6.7 -22 – 9 0.398 Parity 1.3 0.5 – 3.5 0.627 STI history 0.2 -0.0 – 0.09 0.489 HIV 1.2 0.8 – 1.9 0.446 HPV31 Age 1.0 1.0 – 1.1 0.808 Sexual debut 0.9 0.7 – 1.1 0.340 Parity 0.8 0.6 – 1.0 0.063 STI history 2.3 0.8 – 6.3 0.117 HIV 0.8 0.3 – 2.3 0.664 HPV33 Age 1.0 0.9 – 1.0 0.391 Sexual debut 1.0 0.8 – 1.2 0.746 Parity 1.0 0.8 – 1.3 0.668 STI history 1.2 0.5 – 3.0 0.684 HIV 0.4 0.2 – 1.1 0.079 HPV35 Age 1.2 0.9 – 1.5 0.341 Sexual debut 0.7 0.3 – 1.4 0.312 Parity 1.0 -4.0 – 6.0 0.683 STI history 0.0 -0.0 – 0.10 0.576 HIV 0.8 0.5 – 1.3 0.447 HPV39 Age 1.0 1.0 – 1.1 0.307 Sexual debut 1.2 0.9 – 1.4 0.148 Parity 1.0 0.7 – 1.3 0.761 STI history 1.4 0.4 – 5.1 0.649 HIV 2.1 0.5 – 8.8 0.295 HPV45 Age 1.1 0.82 – 1.44 0.551 Sexual debut 0.9 0.60 – 1.24 0.414 Parity 1.2 0.45 – 3.39 0.681 STI history 0.3 -0.76 – 1.33 0.566 HIV 1.1 0.4 – 2.8 0.854 HPV51 Age 1.1 0.88 -1.31 0.480 Sexual debut 0.7 0.25 – 1.7 0.374 Parity 1.1 0.36 – 3.54 0.834 STI history 1.0 -0.24 – 0.52 0.424 HIV 1.9 0.7 - 4.7 0.179 HPV52 Age 1.1 0.85 – 1.52 0.382 Sexual debut 0.9 0.50 – 1.50 0.579 Parity 0.5 0.09 – 3.18 0.487 STI history 0.3 -0.21 – 0.71 0.242 HIV 0.8 0.2 – 2.9 0.731 HPV58 Age 1.0 1.0 – 1.1 0.209 Sexual debut 1.0 0.9 – 1.2 0.800 Parity 1.0 0.8 – 1.2 0.661 STI history 0.8 0.3 – 2.0 0.573 HIV 2.5 1.0 – 6.2 0.051 HPV58 Age 1.1 0.86 – 1.44 0.419 Sexual debut 0.7 0.25 – 1.67 0.374 Parity 1.1 0.44 – 2.79 0.822 STI history 0.0 -0.14 – 0.23 0.611 HIV 1.6 0.8 – 3.4 0.194 HPV59 Age 0.1 -0.08 – 0.24 0.198 Sexual debut 1.0 0.88 – 1.22 0.650 Parity -0.8 -2.53 – 1.03 0.272 STI history 0.7 -0.70 – 2.03 0.219 HIV 3.7 0.4 – 35.72 0.262 HPV66a Age 1.1 0.81 – 1.57 0.473 Sexual debut 1.0 0.81 – 1.21 0.959 Parity 1.0 -0.31 – 0.54 0.369 HIV 1.2 0.1 – 19.47 0.894 HPV68 Age 1.1 0.83 – 1.39 0.594 Sexual debut 1.1 0.91 – 1.29 0.382 Parity 1.2 0.49 – 2.94 0.685 STI history 0.3 -0.61 – 1.28 0.420 HIV 1.5 0.40 – 5.79 0.535 Number of HPV infections Age 1.0 0.95 – 1.04 0.802 Sexual debut 0.9 0.82 – 1.01 0.085 Parity 1.0 0.76 – 1.20 0.690 STI history 0.5 0.14 – 1.62 0.239 HIV 1.5 0.42 – 5.13 0.545 Note: STI, sexually transmitted infection; CI, confidence interval; a – no individual with HPV genotype had STI history Reviewer #2: 1. It would be informative to provide a brief description of the HPV vaccination program and uptake in Zimbabwe early in the introduction. The coverage for the HPV prophylactic vaccines is in its infancy in most developing countries, where the coverage is estimated to be more than 12-fold lower than developed countries [10]. As a matter of interest countries such as Zambia, Malawi and Zimbabwe, where the highest global cervical cancer cases are recorded, are still in the pilot and early implementation phases of the national HPV vaccination programs [11-12]. 2. Could the authors clarify the reasons of only including cervical cancer diagnosed at stage 1b-4. Thank you for noting this, we have clarified the selection criteria for our cohort. Our study recruited individuals from an outpatient radiotherapy and chemotherapy treatment facility, therefore, only patients seeking this type of care attend the clinics. Consequently, this excludes patients receiving surgical interventions only, or are receiving palliative care, because these individuals receive care from other oncological units in the hospital. The methods describe this as: The participants from the current study were nested in a pharmacogenomics of cervical cancer study, aiming to recruit women who were newly diagnosed with cervical cancer, and were eligible to receive radical therapy. Potential study participants were identified through the RTC hospital registry. To be considered eligible for this study, women had to be ≥18 years, with histologically confirmed diagnoses of invasive cervical cancer staged between 1b – 4A, and were earmarked for curative anti-cancer therapy. Individuals who were diagnosed with resectable (stage 1A) disease that did not require chemo/radio- therapies, or with advanced disease that required palliative care (stage 4B) were excluded from the study, because these individuals were referred for care outside of the RTC. 3. It seems the histopathological characteristics are available for all cases included in this study. Such information should be included in the descriptive analysis This descriptive data is now included in the demographics table (Table 1) as illustrated below. Tumour Histology Combined n(prop) HIV – n(prop) HIV + n(prop) P Squamous Cell 207 (0.80) 115 (0.83) 92 (0.77) Ref. Adenocarcinoma 25 (0.10) 14 (0.10) 11 (0.09) 0.950b Adenosquamous 11 (0.04) 2 (0.01) 9 (0.08) 0.017 b Other* 15 (0.06) 8 (0.06) 7 (0.06) 0.900b Other= spindle cell carcinoma, papillary serous carcinoma, adenoid cystic, adenosarcoma, small cell carcinoma. 4. Maybe only relevant covariables to the current study are needed to be described. Some of the information collected through the project but not used for the study might not be necessary to mention, such as weight, height, comorbidities and treatment etc. Thank you for this observation. All variables that are not further analysed in this study have been deleted. The amended statement reads: Demographic information such as age, residency, histopathological tumour characteristics, were collected from the patient folder in the RTC. In addition, behavioral and lifestyle factors were collected by interviewing the study participants, namely history of alcohol, smoking and parity. Sexual history information including age at sexual debut, number of sexual partners, history of circumcised partner, sexually transmitted infections were also collected. Data on HIV status was also collected for comparative analysis. 5. I figure no significant association was detected in the univariate regression between HPV-related risk factors (i.e., age, sexual debut, parity and STI history) and any HR-HPV genotypes might be due to limited power, when the HR-HPV types were stratified by each type. However, those are known factors that associated with HPV infection. Could the authors provide estimates (figure 3b) additionally adjusting for those factors and histology at least as sensitivity analysis when examine the co-occurrence of HPV types. Besides, please clarify what is the reference group for the ORs. As observed by the reviewer, these analyses had not been performed due to a lack of association detected in the univariate analysis. To ensure that these findings were not influenced by limited power of study, multivariable regression was performed using the HPV co-occurrences as predictors, and adjusting for the known HPV risk factors- age, sexual debut, parity, STI history and HIV status, and the findings were tabulated into Supplementary Table 3. Although there were no definitive indicators determined in this sensitivity analyses, we did observe a tendency towards of the HPV16/18 co-occurrence to be influences by age HIV status and age of sexual debut. A larger cohort would be needed to confirm the validity of the potential trend observed here. Supplementary Table 3. Multivariate regression analysis of co-occurring HPV genotypes with risk factors. Co-variates OR (95% CI) P HPV16/18 Age 1.0 (1.0 – 1.1) 0.684 HIV 2.3 (0.9 -5.6) 0.065 STI history 0.5 (0.2 – 1.3) 0.159 Parity 1.1 (0.9 – 1.4) 0.274 Age of sexual debut 1.1 (1.0 – 1.3) 0.076 HPV16/33 Age 1.0 (0.9 – 1.0) 0.547 HIV 0.4 (0.1 – 1.5) 0.174 STI history 1.0 (0.2 – 3.9) 0.956 Parity 1.0 (0.7 – 1.3) 0.821 Age of sexual debut 1.0 (0.8 – 1.2) 0.834 HPV16/35 Age 1.0 (1.0 – 1.1) 0.152 HIV 0.8 (0.4 – 1.6) 0.573 STI history 1.1 (0.7 – 2.2) 0.769 Parity 1.0 (0.9 – 1.2) 0.985 Age of sexual debut 1.0 (0.9 – 1.2) 0.532 HPV35/51 Age 1.0 (1.0 – 1.1) 0.282 HIV 1.0 (0.2 – 4.4) 0.999 STI history 3.0 (0.8 – 12.2) 0.115 Parity 0.9 (0.7 – 1.3) 0.670 Age of sexual debut 1.0 (0.8 – 1.3) 0.856 HPV35/52 Age 1.0 (0.8 – 1.3) 0.930 HIV NA NA STI history NA NA Parity 0.9 (0.3 – 3.4) 0.933 Age of sexual debut 1.5 (0.7 – 3.6) 0.332 HPV39/51 Age 1.0 (0.8 – 1.2) 0.827 HIV NA NA STI history NA NA Parity 1.2 (0.7 – 2.0) 0.602 Age of sexual debut 1.0 (0.5 – 1.9) 0.984 HPV39/56 Age 1.2 (1.0 – 1.4) 0.108 HIV NA NA STI history NA NA Parity 1.2 (0.7 – 2.3) 0.520 Age of sexual debut 1.2 (0.7 – 2.3) 0.582 6. A legend explaining how the HR-HPV types were classified (ie. hierarchical classification) especially for those cases with multiple types of HPV infection in table 1 could be informative. Thank you for this recommendation. In our analysis, HPVs were only analysed at a genotype level, due to the limited coverage of the HPV genotyping assay used to test for HPV DNA. We have clarified this in the methods section of the manuscript, and have also included a figure legend in the results for reference to phylogenetic clades in the discussion section. Methods section: For analysis all individual HPV genotypes regardless of whether they occur as single or multiple infections were analysed were reported as standalone genotypes. None of the statistical analysis taking into account the species from which the HPV genotypes are from. Results section: a= Human papillomavirus alpha 9 species; b= Human papillomavirus alpha 7 species; c= Human papillomavirus alpha 5 species; d= Human papillomavirus alpha 6 species. 7. In table 4, could the authors clarify the data source for the HPV types in each region of Africa if they are from external studies? Thank you for this comment. We have clarified in the results section where we obtained the data from. The prevalence of the various HPV genotypes in the Zimbabwean study cohort was compared to the most common HPV genotypes on other African women across the continent, using data obtained from HPV Information Centre database (https://hpvcentre.net). 8. Could the authors provide a detailed descriptive table as supplement the distribution of HR-HPV types by HIV status for all included women (including the specific types for multiple infections)? The additional data for the HPV multiple infections by HIV status was collated into a supplementary table 2. Further inclusion of more than 2 HR-HPVs Attachments Attachment Submitted filename: PLOS Repsonses to reviewers_14Apr2021.docx* https://doi.org/10.1371/journal.pone.0257324.r002
12 Aug 2021 Decision Letter - Graciela Andrei, Editor PONE-D-21-04071R1 High-Risk HPV genotypes in Zimbabwean women with cervical cancer: Comparative Analyses between HIV-negative and HIV-positive women. PLOS ONE Dear Dr. Dandara, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. ============================== Please take into account the concerns raised by Reviewer #2 after the first round of revision. ============================== Please submit your revised manuscript by Sep 26 2021 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org. 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You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: (No Response) Reviewer #2: Thank you for the extensive work from the authors in addressing the comments, and manuscript has been substantially improved. However, there are a couple responses to the comments could be further clarified: In the response to comment point 5, the author has already performed a multivariate regression analysis, using the HPV genotypes as predictors, while controlling for age and HIV status, and the ORs for significant HPV genotypes were illustrated in fig 3b. Therefore, the sensitivity analysis is expecting to be repeating exact the same regression model by additionally control for factors of sexual debut, parity, STI history and histology and presented the ORs as a supplementary figure or table instead of presenting ORs for each of the covariate as shown in the current supplementary table 3. I appreciate the work done by the authors for supplementary table 2, however, what would be informative to address the comments point 8 is to provide a simple frequency table showing the distribution of hrHPV types, including both single type infection and multiple types of infection by HIV status (HIV positive and HIV negative). Considering there are a proportion of women had more than 2 types of HPV infection (table 2), showing the actual HPV types by HIV status could be interesting to the readership. ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). 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Revision 2
24 Aug 2021 Author Response Response to Reviewer Comments: PONE-D-21-04071R1 24 August 2021, Dear Professor Graciela Andrei Thank you for reviewing our manuscript entitled “High-Risk HPV genotypes in Zimbabwean women with cervical cancer: Comparative Analyses between HIV-negative and HIV-positive women” and providing us with constructive criticism on how to improve the statistical analysis and the scientific soundness of the work. Below are our responses to each of the reviewers’ and editor’s comments; Reviewer #2: Thank you for the extensive work from the authors in addressing the comments, and manuscript has been substantially improved. However, there are a couple responses to the comments could be further clarified. In the response to comment point 5, the author has already performed a multivariate regression analysis, using the HPV genotypes as predictors, while controlling for age and HIV status, and the ORs for significant HPV genotypes were illustrated in fig 3b. Therefore, the sensitivity analysis is expecting to be repeating exact the same regression model by additionally control for factors of sexual debut, parity, STI history and histology and presented the ORs as a supplementary figure or table instead of presenting ORs for each of the covariate as shown in the current supplementary table 3. Thank you for further clarifying the expectations of the reviewer, which the authors may have misunderstood in the previous peer review process. The authors have done the best they can to address this comment. To this effect, S3 Table was added, consisting of multivariate analysis for the co-segregation of the HPV genotypes, taking into consideration the proposed covariates, namely, age, history of STI, parity, HIV status, age of sexual debut, tumour histology, as suggested. The comment was addressed in the manuscript to read: In order to ensure that lack of significance observed was not a result of low study power, a sensitivity appraisal was conducted, using multivariate regression analyses controlling for age, history of sexually transmitted infections, parity, HIV status, age at sexual debut and tumour histology. In this sensitivity analyses, all the co-segregation patterns remained statistically significant except HPV16/33 (OR=0.4; 95% CI=0.2-1.9; p=0.05), HPV35/52 (OR=0.5; 95% CI=0.1-4.3; p=0.50) (S3 Table). Table S3. Sensitivity analysis for HPV co-segregation. HPV genotypes* OR (95% CI) P 16/18 0.3 (0.1-0.5) <0.01 16/33 0.4 (0.2-1.0) 0.05 16/35 3.6 (1.8-7.2) <0.01 35/51 8.8 (2.3-34.3) <0.01 35/52 0.5 (0.1-4.3) 0.50 39/51 4.2 (0.7-25.9) 0.12 39/56 9.5 (1.1-82.9) 0.04 multivariate analysis for the co-segregation of HPV genotypes, taking into consideration age, history of STI, parity, HIV status, age of sexual debut, tumour histology. I appreciate the work done by the authors for supplementary table 2, however, what would be informative to address the comments point 8 is to provide a simple frequency table showing the distribution of hrHPV types, including both single type infection and multiple types of infection by HIV status (HIV positive and HIV negative). Considering there are a proportion of women had more than 2 types of HPV infection (table 2), showing the actual HPV types by HIV status could be interesting to the readership. Thank you for indicating which analyses and data would be more interesting to the readers. The comments were received well and taken into consideration. The authors have amended the table to report on absolute frequencies, by HIV status, as shown below. This tabulation was favoured as it clearly represents the number of individuals with specific HPV genotypes depending on HIV status. S2 Table. The number of individuals harbouring specific HPV genotypes stratified by HIV status. Number of HPVs (n) HPV genotype HIV status 1 2 3 4 5 6 16 - 19 18 5 1 0 0 + 15 13 3 1 1 0 18 - 13 12 1 0 1 1 + 6 13 1 0 0 0 31 - 1 0 1 2 0 0 + 1 0 0 0 0 1 33 - 2 0 1 2 0 0 + 2 0 0 0 0 0 35 - 15 15 3 0 1 0 + 3 10 3 0 1 1 39 - 0 2 0 1 0 0 + 0 1 0 0 0 0 45 - 1 0 2 3 0 0 + 0 0 1 1 0 0 51 - 0 0 1 0 1 0 + 1 1 1 1 1 1 52 - 1 2 1 0 0 0 + 0 3 1 0 0 1 56 - 0 0 0 1 0 0 + 0 0 1 0 1 0 58 - 0 2 1 1 1 0 + 0 2 0 0 1 0 59 - 0 0 0 2 0 0 + 2 0 1 1 0 0 66 - 0 0 0 1 0 0 + 0 0 1 0 0 0 68 - 2 0 1 0 1 0 + 1 0 1 1 2 1 TOTAL 85 94 31 19 12 6 Attachments Attachment Submitted filename: PONE-D-21-04071R1-responses to reviewers 24082021.docx* https://doi.org/10.1371/journal.pone.0257324.r004
31 Aug 2021 Decision Letter - Graciela Andrei, Editor High-Risk HPV genotypes in Zimbabwean women with cervical cancer: Comparative Analyses between HIV-negative and HIV-positive women. PONE-D-21-04071R2 Dear Dr. Dandara, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Graciela Andrei Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. If the authors have adequately addressed your comments raised in a previous round of review and you feel that this manuscript is now acceptable for publication, you may indicate that here to bypass the “Comments to the Author” section, enter your conflict of interest statement in the “Confidential to Editor” section, and submit your "Accept" recommendation. Reviewer #1: All comments have been addressed Reviewer #2: All comments have been addressed ******** 2. Is the manuscript technically sound, and do the data support the conclusions? The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: (No Response) Reviewer #2: (No Response) ****** 3. Has the statistical analysis been performed appropriately and rigorously? Reviewer #1: (No Response) Reviewer #2: (No Response) ****** 4. Have the authors made all data underlying the findings in their manuscript fully available? The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified. Reviewer #1: (No Response) Reviewer #2: (No Response) ****** 5. Is the manuscript presented in an intelligible fashion and written in standard English? PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here. Reviewer #1: (No Response) Reviewer #2: (No Response) ****** 6. Review Comments to the Author Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. (Please upload your review as an attachment if it exceeds 20,000 characters) Reviewer #1: (No Response) Reviewer #2: (No Response) ****** 7. PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review?** For information about this choice, including consent withdrawal, please see our Privacy Policy. Reviewer #1: No Reviewer #2: No https://doi.org/10.1371/journal.pone.0257324.r005
Formally Accepted
16 Sep 2021 Acceptance Letter - Graciela Andrei, Editor PONE-D-21-04071R2 High-Risk HPV genotypes in Zimbabwean women with cervical cancer: Comparative Analyses between HIV-negative and HIV-positive women. Dear Dr. Dandara: I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact onepress@plos.org. If we can help with anything else, please email us at plosone@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Graciela Andrei Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0257324.r006

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