Analysis of the effectiveness and efficiency of the    Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study

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Remarkably, 30% of these cases exhibit an undetected primary lesion. Hence, categorizing them as MBD of unknown origin. The diagnostic processes of patients with MBD of unknown origin typically takes up to four months, rendering it as a catastrophic disease with the second-highest financial burden. Given its urgency, it is necessary to develop a evidence-based consensus for managing cases of MBD with an unknown origin. Purpose This study aimed to enhance the effectiveness and efficiency of treating patients with MBD of unknown origin through the application of the INA-MBD algorithm. Research method A quasi-experimental study with a pretest and post-test design was conducted with a total of 128 patients who met the inclusion and exclusion criteria. The patients were consecutively enrolled and categorized into two groups: the intervention group with the INA-MBD algorithm and the non-intervention group without the INA-MBD algorithm. The primary outcomes were the cost and time to diagnose MBD of unknown origin. The proposed measuring tool was the INA-MBD algorithm. Furthermore, for the cost-to-diagnosis variable, an extra measurement tool was used, which were summaries of the patient’s medical bill including hospital stays and medical procedures. The analysis of data related to the time-to-diagnosis variable was conducted using the Log Rank regression test, and cost-to-diagnosis variable was carried out using co-variance test. " } { "@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/13-333/v2", "name": "Analysis of the effectiveness and efficiency of the Indonesian metastatic..." } } ] } Home Browse Analysis of the effectiveness and efficiency of the Indonesian metastatic... ALL Metrics - Views Downloads Get PDF Get XML Cite How to cite this article Putro YAP, Aryandono T, Widodo I et al. Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.12688/f1000research.146118.2 ) 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 ▬ ✚ Study Protocol Revised Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] Yuni Artha Prabowo Putro 1,2 , Teguh Aryandono 1 , Irianiwati Widodo 1 , [...] Rahadyan Magetsari 1,2 , Dibyo Pramono 1,3 , Muhammad Phetrus Johan https://orcid.org/0000-0002-5567-4710 4,5 , Moh Asri Abidin 6 , Ardanariswara Wikantyasa 2 , A Faiz Huwaidi 2 , Paramita Ayu Saraswati 2 Yuni Artha Prabowo Putro 1,2 , Teguh Aryandono 1 , [...] Irianiwati Widodo 1 , Rahadyan Magetsari 1,2 , Dibyo Pramono 1,3 , Muhammad Phetrus Johan https://orcid.org/0000-0002-5567-4710 4,5 , Moh Asri Abidin 6 , Ardanariswara Wikantyasa 2 , A Faiz Huwaidi 2 , Paramita Ayu Saraswati 2 PUBLISHED 09 Jul 2024 Author details Author details 1 Doctoral Program in Medicine and Health Sciences, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia 2 Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, D.I. Yogyakarta, 55281, Indonesia 3 Faculty of Dentistry, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia 4 Orthopaedic and Traumatology, RSUP Dr. Wahidin Sudirohusodo, Sulawesi Selatan, 90245, Indonesia 5 Faculty of Medicine, Universitas Hasanuddin, Makassar, Sulawesi Selatan, 90245, Indonesia 6 Faculty of Medicine and Health Sciences, Universitas Muhammadiyah Makassar, Makassar, Sulawesi Selatan, 90221, Indonesia Yuni Artha Prabowo Putro Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Supervision, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Teguh Aryandono Roles: Conceptualization, Formal Analysis, Supervision, Validation, Writing – Review & Editing Irianiwati Widodo Roles: Conceptualization, Formal Analysis, Supervision, Validation, Writing – Review & Editing Rahadyan Magetsari Roles: Conceptualization, Formal Analysis, Supervision, Writing – Review & Editing Dibyo Pramono Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Supervision, Validation Muhammad Phetrus Johan Roles: Conceptualization, Methodology, Validation, Writing – Review & Editing Moh Asri Abidin Roles: Conceptualization, Methodology, Supervision, Writing – Review & Editing Ardanariswara Wikantyasa Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Writing – Original Draft Preparation A Faiz Huwaidi Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Software, Writing – Original Draft Preparation Paramita Ayu Saraswati Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Software, Writing – Original Draft Preparation OPEN PEER REVIEW DETAILS REVIEWER STATUS Abstract Background Patients with Metastatic Bone Disease (MBD) often present with complaints of pain and multiple osteolytic lesions findings. Remarkably, 30% of these cases exhibit an undetected primary lesion. Hence, categorizing them as MBD of unknown origin. The diagnostic processes of patients with MBD of unknown origin typically takes up to four months, rendering it as a catastrophic disease with the second-highest financial burden. Given its urgency, it is necessary to develop a evidence-based consensus for managing cases of MBD with an unknown origin. Purpose This study aimed to enhance the effectiveness and efficiency of treating patients with MBD of unknown origin through the application of the INA-MBD algorithm. Research method A quasi-experimental study with a pretest and post-test design was conducted with a total of 128 patients who met the inclusion and exclusion criteria. The patients were consecutively enrolled and categorized into two groups: the intervention group with the INA-MBD algorithm and the non-intervention group without the INA-MBD algorithm. The primary outcomes were the cost and time to diagnose MBD of unknown origin. The proposed measuring tool was the INA-MBD algorithm. Furthermore, for the cost-to-diagnosis variable, an extra measurement tool was used, which were summaries of the patient’s medical bill including hospital stays and medical procedures. The analysis of data related to the time-to-diagnosis variable was conducted using the Log Rank regression test, and cost-to-diagnosis variable was carried out using co-variance test. READ ALL READ LESS Keywords metastatic bone disease, Neoplasm, unknown primary, algorithm, management, cost effectiveness, diagnosis Corresponding Author(s) Yuni Artha Prabowo Putro ( [email protected] ) Close Corresponding author: Yuni Artha Prabowo Putro Competing interests: No competing interests were disclosed. Grant information: The author(s) declared that no grants were involved in supporting this work. Copyright: © 2024 Putro YAP et al . 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: Putro YAP, Aryandono T, Widodo I et al. Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.12688/f1000research.146118.2 ) First published: 23 Apr 2024, 13 :333 ( https://doi.org/10.12688/f1000research.146118.1 ) Latest published: 09 Jul 2024, 13 :333 ( https://doi.org/10.12688/f1000research.146118.2 ) Revised Amendments from Version 1 We have revised our manuscript to incorporate the reviewer's suggestions. In the introduction and methods sections, we detailed our process for synthesizing the INA-MBD algorithm and noted that we conducted preliminary studies in our hospital. We provided the rationale for using retrospective data in the control group and defined the operational criteria for the MBD diagnosis we used. Additionally, we included the research timeline and completed the data collection process. The discussion section now offers a more detailed and comprehensive analysis of our research and relevant literature. We have revised our manuscript to incorporate the reviewer's suggestions. In the introduction and methods sections, we detailed our process for synthesizing the INA-MBD algorithm and noted that we conducted preliminary studies in our hospital. We provided the rationale for using retrospective data in the control group and defined the operational criteria for the MBD diagnosis we used. Additionally, we included the research timeline and completed the data collection process. The discussion section now offers a more detailed and comprehensive analysis of our research and relevant literature. See the authors' detailed response to the review by Kevin Christian Tjandra READ REVIEWER RESPONSES Introduction Patients diagnosed with Metastatic Bone Disease (MBD) of unknown origin are at greater risk of higher mortality and morbidity rates, mainly due to skeletal-related events, with a solely 5% survival rate over 5 years. 1 In three-quarters of MBD cases, the diagnosis of primary malignancy is made after the patient's condition deteriorates, typically around four months into the progression of the disease. 2 Alarmingly, it has been brought to attention that late establishment of the primary cancer diagnosis significantly contributes to treatment delay up to 86%. 3 The prolonged process of diagnosing the unknown origin of MBD is further exacerbated by a series of routine laboratory examinations, including tumor markers. 4 The prognosis of patients with MBD of unknown origin highly relies on the timing of diagnosis and treatment. The primary challenge in managing patients with MBD of unknown origin lies in the absence of consensus on prioritizing supporting examinations. Unfortunately, there is no current guideline on the selection of preliminary examinations to identify primary lesions in MBD. 1 This lack of consensus adds to the financial burden, with Indonesian national health insurance allocating 18% of the total budget for catastrophic diseases to the care of cancer patients. 5 In the United States, the direct cost of MBD is approximately $75,329, double the cost of treating cancer patients without MBD, at $31,382 per year. 6 , 7 Common diagnostic procedures involve a series of laboratory tests such as tumor markers and ALP, X-rays of the chest and affected limbs, CT scans, MRIs, bone scans, and PET scans, followed by bone or organ biopsies. These procedures contribute to prolonged diagnosis times and increased financial burdens, intensifying the complexities associated with addressing MBD-related challenges. Certainly, we have developed the INA-MBD algorithm through a rigorous scientific process. We conducted a systematic review, registered in the research registry with the unique number reviewregistry1457. The results of our review are currently under review in a Scopus-indexed journal. This algorithm provides tailored recommendations for prioritizing supporting examinations based on the patient's clinical condition. Diverging from conventional methods, the examinations in the INA-MBD algorithm are not executed sequentially and exhaustively. The diagnostic and management patterns of this algorithm were preliminarily tested in our hospital with a limited sample. Both in theory and practice, the INA-MBD algorithm has proven effective in reducing the time required to diagnose primary malignancy in MBD cases and in lowering costs due to fewer supporting examinations. The main objective is for an early and secure biopsy to speed up the diagnostic process, leading to reduced further examination costs without compromising the success of diagnosing MBD of unknown origin. Objective : The objective of this study was to assess the impact of implementing the INA-MBD algorithm on the direct treatment costs and the time to diagnose primary malignancy in patients with MBD of unknown origin. Protocol Study design This research employed a quasi-experimental pre-test and post-test design, categorizing participants into an intervention group and a non-intervention group. The intervention group utilized the INA-MBD algorithm for diagnosing patients with MBD of unknown origin, while the non-intervention group used the intra-hospital conventional diagnosis algorithm. Patients and eligibility criteria In this study, the intervention group comprised consecutively collected patients from inpatients, outpatients, and emergency departments diagnosed with MBD of unknown origin until reaching the required sample size. The INA-MBD algorithm was implemented in the intervention group. For the non-intervention group, medical record data from MBD-diagnosed patients with unknown primary lesions between 2018 and 2022 at RSUP Dr. Sardjito (Yogyakarta) and Dr. Wahidin Sudirohusodo (South Sulawesi) were utilized. We opted for retrospective data for the control group due to the limited number of patients with MBD of unknown origin at our center. The diagnosis of MBD was established using radiological examinations, where the primary tumor was unknown, and there was no previous history of malignancy at presentation. The primary malignancy of MBD was confirmed using histopathological examination. Inclusion criteria a. Patients with a final diagnosis of MBD b. Patients without a history of malignancy c. Patients who agreed to participate in the this study and signed the written informed consent form. Exclusion criteria a. Patients with incomplete medical record data b. Patients who did not undergo operative procedures. Study settings This multicentre research was conducted at two tertiary referral hospital in Indonesia, RSUP Dr. Sardjito in Yogyakarta and Dr. Wahidin Sudirohusodo in South Sulawesi. Data collection, management, and analysis Data collection Patients diagnosed with MBD of unknown origin based on clinical and radiological examinations will be consecutively collected. Those meeting the inclusion and exclusion criteria will be included in the sample. Data will be collected using a standardized case report form for each sample and both intervention and control groups. Patients with incomplete medical records will be excluded. Variable Independent variable The INA-MBD algorithm ( Figures 1 and 2 ) will be used as the independent variable. The interventional group will use the INA-MBD algorithm as a management guideline, while the non-interventional group relied on retrospective data from medical records. Figure 1. INA-MBD algorithm without pathological fracture. This figure is our original creation synthesized from both literature and our clinical experience. Show steps and list of management in patients with MBD of unknown origin without pathological fracture. CXR (Chest X-Ray), IHC (Immunohistochemistry), CPC (Clinicopathological conference)/ multidisciplinary team discussion Figure 2. INA-MBD algorithm with pathological fracture. This figure is our original creation synthesized from both literature and our clinical experience. Show steps and list of management in patients with MBD of unknown origin with pathological fracture. CXR (Chest X-Ray), IHC (Immunohistochemistry), CPC (Clinicopathological conference)/multidisciplinary team discussion. Dependent and confounding variable The dependent variables were time-to-diagnosis and cost-to-diagnosis. Confounding variables, such as gender, age, type of primary cancer, and metastatic location, were derived from medical records for the non-interventional group and other various sources for the interventional group. Data analysis Bivariate analysis between time to diagnose or cost to diagnose and the use of the INA-MBD algorithm will employ an independent T-test, with Mann-Whitney as an alternative method if the data exhibit abnormal distribution. For the analysis of time to diagnose, the survival rate will be assessed using Kaplan-Meier and log-rank regression tests. To evaluate the hypothesis concerning the cost to diagnose, a covariance test will be employed to analyse the regression mean of both groups. Confounding variables will be controlled using multivariate analysis. Research timeline Dissemination Upon completion of this study, the findings will be published in a Scopus-indexed journal with a Q2-Q1 quartile ranking. Additionally, the results will be presented at the Continuing Orthopaedic Education meeting held by the Indonesian Orthopaedic Association. Study status The study was in the data collection period and is planned to finish collecting data by December 2024. Registration This research will be registered on Researchregistry.com . Discussion The diagnostic challenge in identifying primary malignancies often leads to patients with MBD of unknown origin being misdiagnosed with primary bone tumors or hematological malignancies. An additional complication is that not all MBD patients have a cancer history, with 71% being diagnosed with their primary malignancy only after a clinical deterioration. 2 Another challenge arises when no fractures are found, or patients have no prior history of cancer, making it difficult to diagnose bone metastasis conditions. 8 This delay can negatively impact prognosis and increase the risk of Skeletal Related Events (SREs), including pathological fractures or spinal cord compression. 1 Therefore, it is crucial to promptly identify the origin of bone metastasis using optimal diagnostic strategies. Various types and modalities of radiological examinations are recommended for diagnosing MBD of unknown origin. Complaints of pain in patients over 50 years old with multiple osteolytic bone lesions with ill-defined borders, with or without pathological fractures, can suggest MBD condition. Hence, routine chest X-rays or imaging of affected lesions should be performed in patients suspected of having MBD of unknown origin. 8 – 11 Other radiological examinations that may be conducted include ultrasound, bone scans, Computed Tomography (CT) scans, Magnetic Resonance Imaging (MRI), and PET scans. However, each type of radiological examination has its conditions and limitations. Katagiri et al. reported that supportive examinations of the gastrointestinal and female reproductive organs often waste time and money, so they are not routinely recommended unless specific symptoms are present. 10 Takagi et al. used whole-body CT scans to obtain general body imaging of patients to replace bone scans. 1 This study reported a high success rate in diagnosis using a combination of medical history, physical examination, chest X-rays, blood tests, and tumor markers. Lawrenz et al. 11 reported that PET/CT scans have poor diagnostic capabilities for MBD of unknown origin, a finding supported by Budak et al., who recommended the use of PET/CT scans only to search for other metastatic lesions, not for diagnosis confirmation. 12 Although bone scans are considered the best technique for early diagnosis of bone metastasis, their high cost means they are not routinely performed. Bone survey can be used as an option to diagnose MBD of unknown origin. The sensitivity of bone surveys in detecting bone lesions ranges only from 44-50%, and it is lower compared to bone scans which have a sensitivity of 78%. However, the detection rate of bone surveys is better than bone scans when accompanied by clinical symptoms suggestive of MBD. The cost of the bone survey is also cheaper, making it still used to evaluate MBD lesions. The use of a bone survey is also recommended to confirm abnormal findings from bone scans. 13 In conclusion, when determining the type of supportive examination to use in diagnosing MBD of unknown origin, besides considering the sensitivity and specificity values, the consequences of the examination should also be taken into account. The results of supportive examinations can directly or indirectly affect a person's health condition and outcomes. Health conditions can be influenced by factors such as the accuracy of diagnosis, the success of therapy, or psychological conditions, which are influenced by the cost of diagnostic tests or the amount of management costs given to patients. Tsukamoto et al. (2021) advocate the diagnostic algorithm for diagnosing MBD of unknown origin. 14 Plain X-rays, CT scans, and MRI for all patients with bone lesions. If bone destruction is observed without periosteal reaction, then metastasis is suspected, prompting further examinations like abdominal, thoracic, or pelvic CT scans, tumor markers, serum electrophoresis, Bence Jones protein, and bone scans or PET/CT scans. Biopsy is reserved for the conclusion after completing all imaging and laboratory examinations. 8 Tumor marker examinations, including CEA, CA-125, CA19-1, and AFP, exhibit low sensitivity and specificity in determining the primary malignancy in MBD of unknown origin. Tumor markers are not exclusively produced by malignant cells, making serum tumor markers more relevant for therapy monitoring or determining cancer prognosis 4 , 14 More invasive examinations, such as biopsy, can confirm the origin of the primary malignancy in MBD patients. Biopsy can be performed on metastatic bone lesions, with or without pathological fractures, and on lesions suspected to be primary malignancies. Bone biopsies can confirm the origin of malignancy up to 70%. 15 We have devised an algorithm named INA-MBD through clinical and evidence-based methods. The INA-MBD algorithm offers guidelines for managing patients with MBD of unknown origin, in concordance with the patient's clinical condition, whether or not pathological fractures are present. This aims to provide more selective guidance in choosing imaging modalities. The INA-MBD algorithm excludes serum tumor marker examinations as a diagnostic tool for the reasons explained above. It also serves as a guide for performing biopsies not only on suspected primary lesions but also on bone lesions. The measurable variables representing the effectiveness of the INA-MBD algorithm include time-to-diagnosis and the cost-effectiveness of managing patients with MBD of unknown origin. This research aims to establish the INA-MBD algorithm as an evidence-based alternative for managing MBD of unknown origin. The utilization of the INA-MBD algorithm is expected to improve outcomes for patients with MBD of unknown origin and alleviate the financial burden associated with management. Ethical considerations This study has Ethical approval from The Medical and Health Research Ethics Committee (MHREC) Faculty of Medicine, Public Health and Nursing Universitas Gadjah Mada- Dr. Sarjito General Hospital on 09 Jan 2023 and the protocol number is KE/FK/0042/EC/2023 Patients who agreed to participate in the study signed the written consent form. Author contributions Conceptualization: (Y.A.P., A.W., T.A., I., R.M., D.P.) Data Curation: (Y.A.P., D.P., A.W., P.A.S., A.F.) Formal Analysis: (Y.A.P.)., A.W., T.A., I., R.M., D.P) Investigation: (Y.A.P., A.W., P.A.S., A.F) Methodology: (Y.A.P., D.P., A.W., M.P.J., M.A.A.) Software: (Y.A.P., P.A.S., A.F.) Supervision: (T.A., I., RM., D.P., M.P.J., M.A.A.) Validation: (Y.A.P., T.A. I., R.M., D.P., M.P.J., M.A.A.) Writing original draft: (Y.A.P., A.W., P.A.S., A.F.) Writing review & editing: Y.A.P., T.A., I., R.M., D.P., M.P.J., M.A.A., A.W., P.A.S., A.F.). Data availability Underlying data No data are associated with this article. Extended data Spirit Outcome Checklist is available at Zenodo: Checklist for” Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD) time to diagnosis and cost to diagnosis: Quasi Experimental Study” , DOI 10.5281/zenodo.10901731 . 16 Data are available under the terms of the Creative Commons Attribution 4.0 International license (CC BY 4.0). References 1. Takagi T, Katagiri H, Kim Y, et al. : Skeletal metastasis of unknown primary origin at the initial visit: A retrospective analysis of 286 cases. PLoS One. 2015; 10 (6): e0129428. PubMed Abstract | Publisher Full Text | Free Full Text 2. Kitagawa Y, Yamaoka T, Yokouchi M, et al. : Diagnostic Value of Plain Radiography for Symptomatic Bone Metastasis at the First Visit. J. Nippon. Med. Sch. 2018; 85 (6): 315–321. Publisher Full Text Reference Source 3. Gondhowiardjo S, Hartanto S, Wirawan S, et al. : Treatment delay of cancer patients in Indonesia: A reflection from a national referral hospital. Med. J. Indones. 2021; 30 (2): 129–137. Publisher Full Text 4. Perkins GL, Slater ED, Sanders GK, et al. : Serum Tumor Markers - American Family Physician.2003. Reference Source 5. Budi E, Juniartha P, Pinem R, et al. : Heru Ganes Santoso.2020. 6. DiCaprio MR, Murtaza H, Palmer B, et al. : Narrative review of the epidemiology, economic burden, and societal impact of metastatic bone disease. Ann. Jt. 2022; 7 : 28. PubMed Abstract | Publisher Full Text | Free Full Text 7. Schulman KL, Kohles J: Economic burden of metastatic bone disease in the U.S. Cancer. 2007; 109 (11): 2334–2342. Publisher Full Text 8. Kim W, Han I, Kang S, et al. : Non-spine bone metastasis as an initial manifestation of cancer in Korea.J. Korean Med. Sci.2014; 29 : 357–362. PubMed Abstract | Publisher Full Text | Free Full Text 9. Ugras N, Ulviye Y, Akesen B, et al. : Solitary bone metastases of unknown origin. Acta Orthop. Belg. 2014; 80 : 139–143. PubMed Abstract 10. Katagiri H, Takahashi M, Inagaki J, et al. : Determining the Site of the Primary Cancer in Patients with Skeletal Metastasis of Unknown Origin: A Retrospective Study. Cancer. 1999; 86 (3): 533–537. <a target="xrefwindow" id="d352811e811" href="https://doi.org/10.1002/(SICI)1097-0142(19990801)86:3 Publisher Full Text 11. Lawrenz JM, Gordon J, George J, et al. Does PET/CT Aid in Detecting Primary Carcinoma in Patients with Skeletal Metastases of Unknown Primary?Clin. Orthop. Relat. Res.2020; 478 : 2451–2457. PubMed Abstract | Publisher Full Text | Free Full Text 12. Budak E, Yanarateş A: Role of 18F-FDG PET/CT in the detection of primary malignancy in patients with bone metastasis of unknown origin . Rev. Esp. Med. Nucl. Imagen. Mol. 2020; 39 (1): 14–19. PubMed Abstract | Publisher Full Text 13. O’Sullivan GJ: Imaging of bone metastasis: An update. World J. Radiol. 2015; 7 (8): 202–211. PubMed Abstract | Publisher Full Text | Free Full Text 14. Tsukamoto S, Kido A, Tanaka Y, et al. : Current overview of treatment for metastatic bone disease. Curr. Oncol. 2021; 28 (5): 3347–3372. PubMed Abstract | Publisher Full Text | Free Full Text 15. Datir A, Pechon P, Saifuddin A: Imaging-guided percutaneous biopsy of pathologic fractures: A retrospective analysis of 129 cases. Am. J. Roentgenol. 2009; 193 (2): 504–508. PubMed Abstract | Publisher Full Text 16. Huwaidi AF: Spirit Outcome Checklist for INA-MBD. Zenodo. [Dataset]. 2024. Publisher Full Text Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 23 Apr 2024 ADD YOUR COMMENT Comment Author details Author details 1 Doctoral Program in Medicine and Health Sciences, Faculty of Medicine, Public Health and Nursing, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia 2 Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, D.I. Yogyakarta, 55281, Indonesia 3 Faculty of Dentistry, Universitas Gadjah Mada, Yogyakarta, D.I. Yogyakarta, 55281, Indonesia 4 Orthopaedic and Traumatology, RSUP Dr. Wahidin Sudirohusodo, Sulawesi Selatan, 90245, Indonesia 5 Faculty of Medicine, Universitas Hasanuddin, Makassar, Sulawesi Selatan, 90245, Indonesia 6 Faculty of Medicine and Health Sciences, Universitas Muhammadiyah Makassar, Makassar, Sulawesi Selatan, 90221, Indonesia Yuni Artha Prabowo Putro Roles: Conceptualization, Data Curation, Formal Analysis, Investigation, Methodology, Software, Supervision, Validation, Writing – Original Draft Preparation, Writing – Review & Editing Teguh Aryandono Roles: Conceptualization, Formal Analysis, Supervision, Validation, Writing – Review & Editing Irianiwati Widodo Roles: Conceptualization, Formal Analysis, Supervision, Validation, Writing – Review & Editing Rahadyan Magetsari Roles: Conceptualization, Formal Analysis, Supervision, Writing – Review & Editing Dibyo Pramono Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Supervision, Validation Muhammad Phetrus Johan Roles: Conceptualization, Methodology, Validation, Writing – Review & Editing Moh Asri Abidin Roles: Conceptualization, Methodology, Supervision, Writing – Review & Editing Ardanariswara Wikantyasa Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Writing – Original Draft Preparation A Faiz Huwaidi Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Software, Writing – Original Draft Preparation Paramita Ayu Saraswati Roles: Conceptualization, Data Curation, Formal Analysis, Methodology, Software, Writing – Original Draft Preparation 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: 09 Jul 2024, 13:333 https://doi.org/10.12688/f1000research.146118.2 version 1 Published: 23 Apr 2024, 13:333 https://doi.org/10.12688/f1000research.146118.1 Copyright © 2024 Putro YAP et al . 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. Manager (RIS) Sente metrics Views Downloads F1000Research - - PubMed Central info_outline Data from PMC are received and updated monthly. - - Citations open_in_new 0 open_in_new 0 open_in_new SEE MORE DETAILS CITE how to cite this article Putro YAP, Aryandono T, Widodo I et al. Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.12688/f1000research.146118.2 ) NOTE: If applicable, it is important to ensure the information in square brackets after the title is included in all citations of this article. COPY CITATION DETAILS track receive updates on this article Track an article to receive email alerts on any updates to this article. TRACK THIS ARTICLE Share Open Peer Review Current Reviewer Status: ? Key to Reviewer Statuses VIEW HIDE 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 Version 2 VERSION 2 PUBLISHED 09 Jul 2024 Revised Views 0 Cite How to cite this report: Santos JC. Reviewer Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r341851 ) The direct URL for this report is: https://f1000research.com/articles/13-333/v2#referee-response-341851 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 28 Nov 2024 Joana Cristo Santos , Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal Approved VIEWS 0 https://doi.org/10.5256/f1000research.167763.r341851 The article presents a study designed to enhance the effectiveness and efficiency of diagnosing and treating patients with MBD by proposing a pseudo-algorithm and examining the relationships between cost-to-diagnosis and time-to-diagnosis. The article is well-structured and offers ... Continue reading READ ALL The article presents a study designed to enhance the effectiveness and efficiency of diagnosing and treating patients with MBD by proposing a pseudo-algorithm and examining the relationships between cost-to-diagnosis and time-to-diagnosis. The article is well-structured and offers an innovative approach to improving MBD diagnosis, which could have significant implications for clinical practice. The focus on both cost and time metrics adds practical value to the research, making it highly relevant to healthcare systems aiming to optimize resource allocation. However, there are a few areas that could benefit from further elaboration. For instance, the description of the control group lacks detail. Knowing how many patients were included and their demographics would be helpful. Additionally, the methodology would benefit from a clearer explanation of how key variables, such as cost and time, will be measured and analyzed. These details would strengthen the study's credibility and provide a more comprehensive understanding for readers. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Yes Are the datasets clearly presented in a useable and accessible format? Not applicable Competing Interests: No competing interests were disclosed. Reviewer Expertise: Meta-Analysis; Oncology Research; Data Science 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 Santos JC. Reviewer Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r341851 ) The direct URL for this report is: https://f1000research.com/articles/13-333/v2#referee-response-341851 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 Views 0 Cite How to cite this report: Zhang W. Reviewer Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r341849 ) The direct URL for this report is: https://f1000research.com/articles/13-333/v2#referee-response-341849 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 22 Nov 2024 Weijie Zhang , Department of Orthopaedic Surgery, Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China Approved VIEWS 0 https://doi.org/10.5256/f1000research.167763.r341849 Metastases of unknown primary origin are observed in a subset of cancer patients. Although the primary tumor site can often be identified with advanced diagnostic tools, the process is time-intensive and imposes a considerable financial burden on patients. The current ... Continue reading READ ALL Metastases of unknown primary origin are observed in a subset of cancer patients. Although the primary tumor site can often be identified with advanced diagnostic tools, the process is time-intensive and imposes a considerable financial burden on patients. The current study has the potential to offer direct evidence to assess whether reorganizing clinical practices for these cases could significantly enhance patient survival outcomes or reduce economic strain. The study design is comprehensive, and I fully support the proposed protocol. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Yes Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Oncology, Molecular Biology, Pathology 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 Zhang W. Reviewer Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r341849 ) The direct URL for this report is: https://f1000research.com/articles/13-333/v2#referee-response-341849 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 Views 0 Cite How to cite this report: Tjandra KC. Reviewer Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r300983 ) The direct URL for this report is: https://f1000research.com/articles/13-333/v2#referee-response-300983 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 10 Jul 2024 Kevin Christian Tjandra , Department of Medicine, Faculty of Medicine, Universitas Diponegoro, Semarang, Central Java, Indonesia Approved VIEWS 0 https://doi.org/10.5256/f1000research.167763.r300983 All the revision points ... Continue reading READ ALL All the revision points have been well resolved Competing Interests: No competing interests were disclosed. Reviewer Expertise: Meta-Analysis, In-Vivo Research, Orthopaedic Research, Oncology Research, Surgery Research, Clinical Research 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 Tjandra KC. Reviewer Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r300983 ) The direct URL for this report is: https://f1000research.com/articles/13-333/v2#referee-response-300983 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 23 Apr 2024 Views 0 Cite How to cite this report: Tjandra KC. Reviewer Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.160158.r273174 ) The direct URL for this report is: https://f1000research.com/articles/13-333/v1#referee-response-273174 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 30 May 2024 Kevin Christian Tjandra , Department of Medicine, Faculty of Medicine, Universitas Diponegoro, Semarang, Central Java, Indonesia Approved with Reservations VIEWS 0 https://doi.org/10.5256/f1000research.160158.r273174 Dear Authors, Thank you for the opportunity given. This is an interesting in silico research. However, several adjustments are required. To summarize, this research aimed to to enhance the diagnosis of Metastatic Bone Disease (MBD) of unknown origin using ... Continue reading READ ALL Dear Authors, Thank you for the opportunity given. This is an interesting in silico research. However, several adjustments are required. To summarize, this research aimed to to enhance the diagnosis of Metastatic Bone Disease (MBD) of unknown origin using the INA-MBD algorithm. Conducted on 128 patients, the quasi-experimental study found that applying the algorithm improved efficiency and reduced costs compared to traditional methods, addressing a high-cost and urgent medical issue. In aim to improving the article, listed below are some concerns that were found so maybe editor can consider doing more review on these matters: Title The title has the clarity and conciseness Abstract Background and purpose: the background abstract is well served. Methods: Key improvements include clarifying that patients were randomized to ensure comparability, specifying that the INA-MBD algorithm is the primary diagnostic tool, and detailing how cost analysis was performed. The research also mentioned adjustments for confounding variables and subgroup analyses to increase the robustness of findings. Additionally, reporting baseline characteristics ensured group comparability and notes on follow-up procedures and criteria for evaluating diagnostic accuracy and efficiency were added. 2. Introduction The introduction could be improved by incorporating a clearer explanation of the INA-MBD algorithm's development process and evidence supporting its effectiveness. Additionally, providing specific examples or preliminary results demonstrating the algorithm's impact on diagnostic speed and cost reduction would strengthen the introduction. This would help establish the relevance and potential benefits of the algorithm more convincingly. 3. Method To improve the research method, provide a detailed description of the INA-MBD algorithm and how it differs from the conventional diagnosis algorithm, explaining the rationale behind selecting the retrospective data for the control group and ensuring comparability with the intervention group. Include a justification for the sample size calculation, considering the expected effect size and statistical power. Clarify the criteria for patients with a final diagnosis of MBD, specifying diagnostic tests or clinical criteria used, and ensure comprehensive exclusion criteria to avoid confounding variables. Detail how data collection was standardized across different settings and time points, ensuring data quality and completeness, especially for the retrospective control group. Expand on how confounding variables were controlled or adjusted for during the analysis, using multivariate analysis techniques to account for potential confounders. Provide a more detailed plan for the statistical analysis, including assumptions checked for the tests used, handling of missing data, and any sensitivity analyses planned. Include a section on ethical considerations, such as IRB approval and measures to ensure patient confidentiality and data security. Elaborate on the dissemination plan, including specific journals or conferences targeted and any plans for sharing findings with participating hospitals and patients. Provide a detailed timeline of the study phases, including data collection, analysis, and dissemination stages, ensuring alignment with the projected completion date. Confirm the study's registration on Researchregistry.com or provide an update if the registration is complete, including the registration number. 4. Discussion In discussing the research, it's crucial to address various aspects for improvement. Firstly, highlighting specific examples or case studies illustrating misdiagnoses of primary bone tumors or hematological malignancies in MBD patients can elucidate the clinical consequences, including treatment delays and prognosis implications. Additionally, elaborating on the evidence-based diagnostic process for primary malignancy in MBD patients, supported by literature, aids in understanding the rationale behind imaging examination sequences and their limitations. Critically analyzing the use of tumor markers in diagnosing primary malignancies provides insights into their sensitivity, specificity, and relevance in clinical practice, supported by relevant studies. Further, detailing the selective use of supportive imaging examinations, with specific criteria for their application, and comparing the diagnostic accuracy, cost-effectiveness, and time efficiency of different modalities, allows for informed decision-making. Discussion on the role of biopsy in confirming primary malignancy origins, including its accuracy, safety, and implications for treatment, should be incorporated, supported by evidence. Introducing the INA-MBD algorithm requires a comprehensive description of its development process, key components, and how it addresses current diagnostic limitations, emphasizing its potential impact in clinical practice. Clear objectives and hypotheses for evaluating the INA-MBD algorithm, along with the methodology for assessing its effectiveness and efficiency, are essential. Additionally, specifying outcome measures, such as time-to-diagnosis and cost-effectiveness, and addressing potential confounding variables in the analysis are crucial. Lastly, discussing the research's implications on clinical practice and healthcare policy, offering recommendations for INA-MBD algorithm implementation, and suggesting areas for future research would provide a comprehensive outlook. 5. Conclusion The conclusion is well-executed 6. Additional Information The additional information provides sufficient information I hope the suggestions above will improve the article to be indexed. Once again, thank you for the opportunity given. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Partly Are sufficient details of the methods provided to allow replication by others? Partly Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests: No competing interests were disclosed. Reviewer Expertise: Meta-Analysis, In-Vivo Research, Orthopaedic Research, Oncology Research, Surgery Research, Clinical Research 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, however I have significant reservations, as outlined above. Close READ LESS CITE CITE HOW TO CITE THIS REPORT Tjandra KC. Reviewer Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.160158.r273174 ) The direct URL for this report is: https://f1000research.com/articles/13-333/v1#referee-response-273174 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 09 Jul 2024 Yuni Artha Prabowo Putro , Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, 55281, Indonesia 09 Jul 2024 Author Response Thank you for your kind responses and suggestions. We have adjusted and improved several parts of our manuscript based on the reviewer's comments. Abstract Methods: This research will ... Continue reading Thank you for your kind responses and suggestions. We have adjusted and improved several parts of our manuscript based on the reviewer's comments. Abstract Methods: This research will be conducted using a quasi-experimental design, meaning the sample will receive the intervention without randomization. We chose this design due to the small number of patients with metastatic bone disease of unknown origin, as indicated by both the literature and our clinical experience. Therefore, we will use retrospective data from electronic medical records for the control group, which did not use INA-MBD as a management algorithm, and prospective data for the intervention group, which will use INA-MBD. This decision was made to ensure we have a sufficient sample size. To assess the cost-effectiveness of the INA-MBD algorithm, we only included and analyzed the costs based on ICD.9 coding. This approach was chosen to minimize rate variations between the two hospitals where our research was conducted. The baseline characteristics of the data samples will be presented descriptively. The data includes initials, age, initial diagnosis, details of supporting examinations, and categorization into control or intervention groups. The final diagnosis will be recorded as the primary malignancy if identified, or as MBD of unknown origin if not identified. The diagnosis of primary malignancy or MBD is based on the histopathological result. Introduction The INA-MBD algorithm was developed through a rigorous scientific process. We conducted a systematic review, registered in the research registry with the unique number reviewregistry1457. The results of our review are currently under review in a Scopus-indexed journal. The diagnostic and management patterns of this algorithm were preliminarily tested in our hospital with a limited sample. Both in theory and practice, the INA-MBD algorithm has proven effective in reducing the time required to diagnose primary malignancy in MBD cases and in lowering costs due to fewer supporting examinations. Method Development of INA-MBD Algorithm The INA-MBD algorithm is a management protocol for MBD of unknown origin, developed based on systematic reviews and our clinical experience treating MBD patients at a tertiary referral hospital. INA-MBD differs from other MBD management algorithms because it tailors subsequent examinations based on whether the patient has experienced a pathological fracture. Additionally, we excluded tumor marker testing from the INA-MBD algorithm due to the low level of evidence supporting their use in diagnosing primary malignancies in MBD cases. Our algorithm incorporates a clinicopathological conference (CPC) as a diagnostic tool. The widely used algorithm by Tsukamoto et al. (Curr. Oncol. 2021, 28(5), 3347-3372; https://doi.org/10.3390/curroncol28050290) significantly differs from the INA-MBD algorithm we propose. Rationale to use retrospective data We used retrospective data for the control group due to the limited number of patients with MBD of unknown origin at our center. Therefore, we employed retrospective data for the control group (where the INA-MBD algorithm had not been applied) and prospective data for the intervention group (where the INA-MBD algorithm was applied). Sample size To determine the sample size, we used the formula for the difference in continuous data between the two groups. With a 95% confidence interval and 80% power, and based on the study by Kitagawa et al. (2018), the time required to diagnose MBD of unknown origin was 16 weeks. The researchers considered a meaningful difference to be 8 weeks. Thus, the minimum sample size needed was 63 per group or 126 in total. Final diagnosis of MBD definition In diagnosing cases of MBD, we used radiological examinations to identify bone lesions where the primary tumor was unknown and there was no previous history of malignancy at presentation. The primary malignancy of MBD was confirmed using the histopathological examination. Data collection Patients diagnosed with MBD of unknown origin based on clinical and radiological examinations will be consecutively collected. Those meeting the inclusion and exclusion criteria will be included in the sample. Data will be collected using a standardized case report form (Supplementary Material) for each sample and both intervention and control groups. Patients with incomplete medical records will be excluded. IRB approval This study has been approved by the Medical and Health Research Ethics Committee (MHREC) of the Faculty of Medicine, Public Health, and Nursing at Universitas Gadjah Mada – Dr. Sardjito General Hospital, with reference number KE/FK/0162/EC/2024. Dissemination plan Upon completion of this study, the findings will be published in a Scopus-indexed journal with a Q2-Q1 quartile ranking. Additionally, the results will be presented at the Continuing Orthopaedic Education meeting held by the Indonesian Orthopaedic Association We have revised our latest manuscript to incorporate the comments and suggestions from the reviewers. Thank you for your kind responses and suggestions. We have adjusted and improved several parts of our manuscript based on the reviewer's comments. Abstract Methods: This research will be conducted using a quasi-experimental design, meaning the sample will receive the intervention without randomization. We chose this design due to the small number of patients with metastatic bone disease of unknown origin, as indicated by both the literature and our clinical experience. Therefore, we will use retrospective data from electronic medical records for the control group, which did not use INA-MBD as a management algorithm, and prospective data for the intervention group, which will use INA-MBD. This decision was made to ensure we have a sufficient sample size. To assess the cost-effectiveness of the INA-MBD algorithm, we only included and analyzed the costs based on ICD.9 coding. This approach was chosen to minimize rate variations between the two hospitals where our research was conducted. The baseline characteristics of the data samples will be presented descriptively. The data includes initials, age, initial diagnosis, details of supporting examinations, and categorization into control or intervention groups. The final diagnosis will be recorded as the primary malignancy if identified, or as MBD of unknown origin if not identified. The diagnosis of primary malignancy or MBD is based on the histopathological result. Introduction The INA-MBD algorithm was developed through a rigorous scientific process. We conducted a systematic review, registered in the research registry with the unique number reviewregistry1457. The results of our review are currently under review in a Scopus-indexed journal. The diagnostic and management patterns of this algorithm were preliminarily tested in our hospital with a limited sample. Both in theory and practice, the INA-MBD algorithm has proven effective in reducing the time required to diagnose primary malignancy in MBD cases and in lowering costs due to fewer supporting examinations. Method Development of INA-MBD Algorithm The INA-MBD algorithm is a management protocol for MBD of unknown origin, developed based on systematic reviews and our clinical experience treating MBD patients at a tertiary referral hospital. INA-MBD differs from other MBD management algorithms because it tailors subsequent examinations based on whether the patient has experienced a pathological fracture. Additionally, we excluded tumor marker testing from the INA-MBD algorithm due to the low level of evidence supporting their use in diagnosing primary malignancies in MBD cases. Our algorithm incorporates a clinicopathological conference (CPC) as a diagnostic tool. The widely used algorithm by Tsukamoto et al. (Curr. Oncol. 2021, 28(5), 3347-3372; https://doi.org/10.3390/curroncol28050290) significantly differs from the INA-MBD algorithm we propose. Rationale to use retrospective data We used retrospective data for the control group due to the limited number of patients with MBD of unknown origin at our center. Therefore, we employed retrospective data for the control group (where the INA-MBD algorithm had not been applied) and prospective data for the intervention group (where the INA-MBD algorithm was applied). Sample size To determine the sample size, we used the formula for the difference in continuous data between the two groups. With a 95% confidence interval and 80% power, and based on the study by Kitagawa et al. (2018), the time required to diagnose MBD of unknown origin was 16 weeks. The researchers considered a meaningful difference to be 8 weeks. Thus, the minimum sample size needed was 63 per group or 126 in total. Final diagnosis of MBD definition In diagnosing cases of MBD, we used radiological examinations to identify bone lesions where the primary tumor was unknown and there was no previous history of malignancy at presentation. The primary malignancy of MBD was confirmed using the histopathological examination. Data collection Patients diagnosed with MBD of unknown origin based on clinical and radiological examinations will be consecutively collected. Those meeting the inclusion and exclusion criteria will be included in the sample. Data will be collected using a standardized case report form (Supplementary Material) for each sample and both intervention and control groups. Patients with incomplete medical records will be excluded. IRB approval This study has been approved by the Medical and Health Research Ethics Committee (MHREC) of the Faculty of Medicine, Public Health, and Nursing at Universitas Gadjah Mada – Dr. Sardjito General Hospital, with reference number KE/FK/0162/EC/2024. Dissemination plan Upon completion of this study, the findings will be published in a Scopus-indexed journal with a Q2-Q1 quartile ranking. Additionally, the results will be presented at the Continuing Orthopaedic Education meeting held by the Indonesian Orthopaedic Association We have revised our latest manuscript to incorporate the comments and suggestions from the reviewers. Competing Interests: The authors state no conflict of interest. Close Report a concern Respond or Comment COMMENTS ON THIS REPORT Author Response 09 Jul 2024 Yuni Artha Prabowo Putro , Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, 55281, Indonesia 09 Jul 2024 Author Response Thank you for your kind responses and suggestions. We have adjusted and improved several parts of our manuscript based on the reviewer's comments. Abstract Methods: This research will ... Continue reading Thank you for your kind responses and suggestions. We have adjusted and improved several parts of our manuscript based on the reviewer's comments. Abstract Methods: This research will be conducted using a quasi-experimental design, meaning the sample will receive the intervention without randomization. We chose this design due to the small number of patients with metastatic bone disease of unknown origin, as indicated by both the literature and our clinical experience. Therefore, we will use retrospective data from electronic medical records for the control group, which did not use INA-MBD as a management algorithm, and prospective data for the intervention group, which will use INA-MBD. This decision was made to ensure we have a sufficient sample size. To assess the cost-effectiveness of the INA-MBD algorithm, we only included and analyzed the costs based on ICD.9 coding. This approach was chosen to minimize rate variations between the two hospitals where our research was conducted. The baseline characteristics of the data samples will be presented descriptively. The data includes initials, age, initial diagnosis, details of supporting examinations, and categorization into control or intervention groups. The final diagnosis will be recorded as the primary malignancy if identified, or as MBD of unknown origin if not identified. The diagnosis of primary malignancy or MBD is based on the histopathological result. Introduction The INA-MBD algorithm was developed through a rigorous scientific process. We conducted a systematic review, registered in the research registry with the unique number reviewregistry1457. The results of our review are currently under review in a Scopus-indexed journal. The diagnostic and management patterns of this algorithm were preliminarily tested in our hospital with a limited sample. Both in theory and practice, the INA-MBD algorithm has proven effective in reducing the time required to diagnose primary malignancy in MBD cases and in lowering costs due to fewer supporting examinations. Method Development of INA-MBD Algorithm The INA-MBD algorithm is a management protocol for MBD of unknown origin, developed based on systematic reviews and our clinical experience treating MBD patients at a tertiary referral hospital. INA-MBD differs from other MBD management algorithms because it tailors subsequent examinations based on whether the patient has experienced a pathological fracture. Additionally, we excluded tumor marker testing from the INA-MBD algorithm due to the low level of evidence supporting their use in diagnosing primary malignancies in MBD cases. Our algorithm incorporates a clinicopathological conference (CPC) as a diagnostic tool. The widely used algorithm by Tsukamoto et al. (Curr. Oncol. 2021, 28(5), 3347-3372; https://doi.org/10.3390/curroncol28050290) significantly differs from the INA-MBD algorithm we propose. Rationale to use retrospective data We used retrospective data for the control group due to the limited number of patients with MBD of unknown origin at our center. Therefore, we employed retrospective data for the control group (where the INA-MBD algorithm had not been applied) and prospective data for the intervention group (where the INA-MBD algorithm was applied). Sample size To determine the sample size, we used the formula for the difference in continuous data between the two groups. With a 95% confidence interval and 80% power, and based on the study by Kitagawa et al. (2018), the time required to diagnose MBD of unknown origin was 16 weeks. The researchers considered a meaningful difference to be 8 weeks. Thus, the minimum sample size needed was 63 per group or 126 in total. Final diagnosis of MBD definition In diagnosing cases of MBD, we used radiological examinations to identify bone lesions where the primary tumor was unknown and there was no previous history of malignancy at presentation. The primary malignancy of MBD was confirmed using the histopathological examination. Data collection Patients diagnosed with MBD of unknown origin based on clinical and radiological examinations will be consecutively collected. Those meeting the inclusion and exclusion criteria will be included in the sample. Data will be collected using a standardized case report form (Supplementary Material) for each sample and both intervention and control groups. Patients with incomplete medical records will be excluded. IRB approval This study has been approved by the Medical and Health Research Ethics Committee (MHREC) of the Faculty of Medicine, Public Health, and Nursing at Universitas Gadjah Mada – Dr. Sardjito General Hospital, with reference number KE/FK/0162/EC/2024. Dissemination plan Upon completion of this study, the findings will be published in a Scopus-indexed journal with a Q2-Q1 quartile ranking. Additionally, the results will be presented at the Continuing Orthopaedic Education meeting held by the Indonesian Orthopaedic Association We have revised our latest manuscript to incorporate the comments and suggestions from the reviewers. Thank you for your kind responses and suggestions. We have adjusted and improved several parts of our manuscript based on the reviewer's comments. Abstract Methods: This research will be conducted using a quasi-experimental design, meaning the sample will receive the intervention without randomization. We chose this design due to the small number of patients with metastatic bone disease of unknown origin, as indicated by both the literature and our clinical experience. Therefore, we will use retrospective data from electronic medical records for the control group, which did not use INA-MBD as a management algorithm, and prospective data for the intervention group, which will use INA-MBD. This decision was made to ensure we have a sufficient sample size. To assess the cost-effectiveness of the INA-MBD algorithm, we only included and analyzed the costs based on ICD.9 coding. This approach was chosen to minimize rate variations between the two hospitals where our research was conducted. The baseline characteristics of the data samples will be presented descriptively. The data includes initials, age, initial diagnosis, details of supporting examinations, and categorization into control or intervention groups. The final diagnosis will be recorded as the primary malignancy if identified, or as MBD of unknown origin if not identified. The diagnosis of primary malignancy or MBD is based on the histopathological result. Introduction The INA-MBD algorithm was developed through a rigorous scientific process. We conducted a systematic review, registered in the research registry with the unique number reviewregistry1457. The results of our review are currently under review in a Scopus-indexed journal. The diagnostic and management patterns of this algorithm were preliminarily tested in our hospital with a limited sample. Both in theory and practice, the INA-MBD algorithm has proven effective in reducing the time required to diagnose primary malignancy in MBD cases and in lowering costs due to fewer supporting examinations. Method Development of INA-MBD Algorithm The INA-MBD algorithm is a management protocol for MBD of unknown origin, developed based on systematic reviews and our clinical experience treating MBD patients at a tertiary referral hospital. INA-MBD differs from other MBD management algorithms because it tailors subsequent examinations based on whether the patient has experienced a pathological fracture. Additionally, we excluded tumor marker testing from the INA-MBD algorithm due to the low level of evidence supporting their use in diagnosing primary malignancies in MBD cases. Our algorithm incorporates a clinicopathological conference (CPC) as a diagnostic tool. The widely used algorithm by Tsukamoto et al. (Curr. Oncol. 2021, 28(5), 3347-3372; https://doi.org/10.3390/curroncol28050290) significantly differs from the INA-MBD algorithm we propose. Rationale to use retrospective data We used retrospective data for the control group due to the limited number of patients with MBD of unknown origin at our center. Therefore, we employed retrospective data for the control group (where the INA-MBD algorithm had not been applied) and prospective data for the intervention group (where the INA-MBD algorithm was applied). Sample size To determine the sample size, we used the formula for the difference in continuous data between the two groups. With a 95% confidence interval and 80% power, and based on the study by Kitagawa et al. (2018), the time required to diagnose MBD of unknown origin was 16 weeks. The researchers considered a meaningful difference to be 8 weeks. Thus, the minimum sample size needed was 63 per group or 126 in total. Final diagnosis of MBD definition In diagnosing cases of MBD, we used radiological examinations to identify bone lesions where the primary tumor was unknown and there was no previous history of malignancy at presentation. The primary malignancy of MBD was confirmed using the histopathological examination. Data collection Patients diagnosed with MBD of unknown origin based on clinical and radiological examinations will be consecutively collected. Those meeting the inclusion and exclusion criteria will be included in the sample. Data will be collected using a standardized case report form (Supplementary Material) for each sample and both intervention and control groups. Patients with incomplete medical records will be excluded. IRB approval This study has been approved by the Medical and Health Research Ethics Committee (MHREC) of the Faculty of Medicine, Public Health, and Nursing at Universitas Gadjah Mada – Dr. Sardjito General Hospital, with reference number KE/FK/0162/EC/2024. Dissemination plan Upon completion of this study, the findings will be published in a Scopus-indexed journal with a Q2-Q1 quartile ranking. Additionally, the results will be presented at the Continuing Orthopaedic Education meeting held by the Indonesian Orthopaedic Association We have revised our latest manuscript to incorporate the comments and suggestions from the reviewers. Competing Interests: The authors state no conflict of interest. Close Report a concern COMMENT ON THIS REPORT Comments on this article Comments (0) Version 2 VERSION 2 PUBLISHED 23 Apr 2024 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 3 Version 2 (revision) 09 Jul 24 read read read Version 1 23 Apr 24 read Kevin Christian Tjandra , Faculty of Medicine, Universitas Diponegoro, Semarang, Indonesia Weijie Zhang , Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China Joana Cristo Santos , University of Coimbra, Coimbra, Portugal 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 © 2024 Santos J. 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. 28 Nov 2024 | for Version 2 Joana Cristo Santos , Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal 0 Views copyright © 2024 Santos J. 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 The article presents a study designed to enhance the effectiveness and efficiency of diagnosing and treating patients with MBD by proposing a pseudo-algorithm and examining the relationships between cost-to-diagnosis and time-to-diagnosis. The article is well-structured and offers an innovative approach to improving MBD diagnosis, which could have significant implications for clinical practice. The focus on both cost and time metrics adds practical value to the research, making it highly relevant to healthcare systems aiming to optimize resource allocation. However, there are a few areas that could benefit from further elaboration. For instance, the description of the control group lacks detail. Knowing how many patients were included and their demographics would be helpful. Additionally, the methodology would benefit from a clearer explanation of how key variables, such as cost and time, will be measured and analyzed. These details would strengthen the study's credibility and provide a more comprehensive understanding for readers. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Yes Are the datasets clearly presented in a useable and accessible format? Not applicable Competing Interests No competing interests were disclosed. Reviewer Expertise Meta-Analysis; Oncology Research; Data Science 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 (0) Santos JC. Peer Review Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r341851) 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/13-333/v2#referee-response-341851 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Zhang W. 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. 22 Nov 2024 | for Version 2 Weijie Zhang , Department of Orthopaedic Surgery, Zhejiang Provincial Key Laboratory of Cancer Molecular Cell Biology, Life Sciences Institute, the Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China 0 Views copyright © 2024 Zhang W. 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 Metastases of unknown primary origin are observed in a subset of cancer patients. Although the primary tumor site can often be identified with advanced diagnostic tools, the process is time-intensive and imposes a considerable financial burden on patients. The current study has the potential to offer direct evidence to assess whether reorganizing clinical practices for these cases could significantly enhance patient survival outcomes or reduce economic strain. The study design is comprehensive, and I fully support the proposed protocol. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Yes Are sufficient details of the methods provided to allow replication by others? Yes Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Oncology, Molecular Biology, Pathology 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 (0) Zhang W. Peer Review Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r341849) 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/13-333/v2#referee-response-341849 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Tjandra K. 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. 10 Jul 2024 | for Version 2 Kevin Christian Tjandra , Department of Medicine, Faculty of Medicine, Universitas Diponegoro, Semarang, Central Java, Indonesia 0 Views copyright © 2024 Tjandra K. 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 All the revision points have been well resolved Competing Interests No competing interests were disclosed. Reviewer Expertise Meta-Analysis, In-Vivo Research, Orthopaedic Research, Oncology Research, Surgery Research, Clinical Research 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 (0) Tjandra KC. Peer Review Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.167763.r300983) 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/13-333/v2#referee-response-300983 keyboard_arrow_left Back to all reports Reviewer Report 0 Views copyright © 2024 Tjandra K. 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. 30 May 2024 | for Version 1 Kevin Christian Tjandra , Department of Medicine, Faculty of Medicine, Universitas Diponegoro, Semarang, Central Java, Indonesia 0 Views copyright © 2024 Tjandra K. 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 Dear Authors, Thank you for the opportunity given. This is an interesting in silico research. However, several adjustments are required. To summarize, this research aimed to to enhance the diagnosis of Metastatic Bone Disease (MBD) of unknown origin using the INA-MBD algorithm. Conducted on 128 patients, the quasi-experimental study found that applying the algorithm improved efficiency and reduced costs compared to traditional methods, addressing a high-cost and urgent medical issue. In aim to improving the article, listed below are some concerns that were found so maybe editor can consider doing more review on these matters: Title The title has the clarity and conciseness Abstract Background and purpose: the background abstract is well served. Methods: Key improvements include clarifying that patients were randomized to ensure comparability, specifying that the INA-MBD algorithm is the primary diagnostic tool, and detailing how cost analysis was performed. The research also mentioned adjustments for confounding variables and subgroup analyses to increase the robustness of findings. Additionally, reporting baseline characteristics ensured group comparability and notes on follow-up procedures and criteria for evaluating diagnostic accuracy and efficiency were added. 2. Introduction The introduction could be improved by incorporating a clearer explanation of the INA-MBD algorithm's development process and evidence supporting its effectiveness. Additionally, providing specific examples or preliminary results demonstrating the algorithm's impact on diagnostic speed and cost reduction would strengthen the introduction. This would help establish the relevance and potential benefits of the algorithm more convincingly. 3. Method To improve the research method, provide a detailed description of the INA-MBD algorithm and how it differs from the conventional diagnosis algorithm, explaining the rationale behind selecting the retrospective data for the control group and ensuring comparability with the intervention group. Include a justification for the sample size calculation, considering the expected effect size and statistical power. Clarify the criteria for patients with a final diagnosis of MBD, specifying diagnostic tests or clinical criteria used, and ensure comprehensive exclusion criteria to avoid confounding variables. Detail how data collection was standardized across different settings and time points, ensuring data quality and completeness, especially for the retrospective control group. Expand on how confounding variables were controlled or adjusted for during the analysis, using multivariate analysis techniques to account for potential confounders. Provide a more detailed plan for the statistical analysis, including assumptions checked for the tests used, handling of missing data, and any sensitivity analyses planned. Include a section on ethical considerations, such as IRB approval and measures to ensure patient confidentiality and data security. Elaborate on the dissemination plan, including specific journals or conferences targeted and any plans for sharing findings with participating hospitals and patients. Provide a detailed timeline of the study phases, including data collection, analysis, and dissemination stages, ensuring alignment with the projected completion date. Confirm the study's registration on Researchregistry.com or provide an update if the registration is complete, including the registration number. 4. Discussion In discussing the research, it's crucial to address various aspects for improvement. Firstly, highlighting specific examples or case studies illustrating misdiagnoses of primary bone tumors or hematological malignancies in MBD patients can elucidate the clinical consequences, including treatment delays and prognosis implications. Additionally, elaborating on the evidence-based diagnostic process for primary malignancy in MBD patients, supported by literature, aids in understanding the rationale behind imaging examination sequences and their limitations. Critically analyzing the use of tumor markers in diagnosing primary malignancies provides insights into their sensitivity, specificity, and relevance in clinical practice, supported by relevant studies. Further, detailing the selective use of supportive imaging examinations, with specific criteria for their application, and comparing the diagnostic accuracy, cost-effectiveness, and time efficiency of different modalities, allows for informed decision-making. Discussion on the role of biopsy in confirming primary malignancy origins, including its accuracy, safety, and implications for treatment, should be incorporated, supported by evidence. Introducing the INA-MBD algorithm requires a comprehensive description of its development process, key components, and how it addresses current diagnostic limitations, emphasizing its potential impact in clinical practice. Clear objectives and hypotheses for evaluating the INA-MBD algorithm, along with the methodology for assessing its effectiveness and efficiency, are essential. Additionally, specifying outcome measures, such as time-to-diagnosis and cost-effectiveness, and addressing potential confounding variables in the analysis are crucial. Lastly, discussing the research's implications on clinical practice and healthcare policy, offering recommendations for INA-MBD algorithm implementation, and suggesting areas for future research would provide a comprehensive outlook. 5. Conclusion The conclusion is well-executed 6. Additional Information The additional information provides sufficient information I hope the suggestions above will improve the article to be indexed. Once again, thank you for the opportunity given. Is the rationale for, and objectives of, the study clearly described? Yes Is the study design appropriate for the research question? Partly Are sufficient details of the methods provided to allow replication by others? Partly Are the datasets clearly presented in a useable and accessible format? Yes Competing Interests No competing interests were disclosed. Reviewer Expertise Meta-Analysis, In-Vivo Research, Orthopaedic Research, Oncology Research, Surgery Research, Clinical Research 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, however I have significant reservations, as outlined above. reply Respond to this report Responses (1) Author Response 09 Jul 2024 Yuni Artha Prabowo Putro, Orthopedics and Traumatology, RSUP Dr. Sardjito Hospital, Jl. Kesehatan Sendowo, , Sleman, 55281, Indonesia Thank you for your kind responses and suggestions. We have adjusted and improved several parts of our manuscript based on the reviewer's comments. Abstract Methods: This research will be conducted using a quasi-experimental design, meaning the sample will receive the intervention without randomization. We chose this design due to the small number of patients with metastatic bone disease of unknown origin, as indicated by both the literature and our clinical experience. Therefore, we will use retrospective data from electronic medical records for the control group, which did not use INA-MBD as a management algorithm, and prospective data for the intervention group, which will use INA-MBD. This decision was made to ensure we have a sufficient sample size. To assess the cost-effectiveness of the INA-MBD algorithm, we only included and analyzed the costs based on ICD.9 coding. This approach was chosen to minimize rate variations between the two hospitals where our research was conducted. The baseline characteristics of the data samples will be presented descriptively. The data includes initials, age, initial diagnosis, details of supporting examinations, and categorization into control or intervention groups. The final diagnosis will be recorded as the primary malignancy if identified, or as MBD of unknown origin if not identified. The diagnosis of primary malignancy or MBD is based on the histopathological result. Introduction The INA-MBD algorithm was developed through a rigorous scientific process. We conducted a systematic review, registered in the research registry with the unique number reviewregistry1457. The results of our review are currently under review in a Scopus-indexed journal. The diagnostic and management patterns of this algorithm were preliminarily tested in our hospital with a limited sample. Both in theory and practice, the INA-MBD algorithm has proven effective in reducing the time required to diagnose primary malignancy in MBD cases and in lowering costs due to fewer supporting examinations. Method Development of INA-MBD Algorithm The INA-MBD algorithm is a management protocol for MBD of unknown origin, developed based on systematic reviews and our clinical experience treating MBD patients at a tertiary referral hospital. INA-MBD differs from other MBD management algorithms because it tailors subsequent examinations based on whether the patient has experienced a pathological fracture. Additionally, we excluded tumor marker testing from the INA-MBD algorithm due to the low level of evidence supporting their use in diagnosing primary malignancies in MBD cases. Our algorithm incorporates a clinicopathological conference (CPC) as a diagnostic tool. The widely used algorithm by Tsukamoto et al. (Curr. Oncol. 2021, 28(5), 3347-3372; https://doi.org/10.3390/curroncol28050290) significantly differs from the INA-MBD algorithm we propose. Rationale to use retrospective data We used retrospective data for the control group due to the limited number of patients with MBD of unknown origin at our center. Therefore, we employed retrospective data for the control group (where the INA-MBD algorithm had not been applied) and prospective data for the intervention group (where the INA-MBD algorithm was applied). Sample size To determine the sample size, we used the formula for the difference in continuous data between the two groups. With a 95% confidence interval and 80% power, and based on the study by Kitagawa et al. (2018), the time required to diagnose MBD of unknown origin was 16 weeks. The researchers considered a meaningful difference to be 8 weeks. Thus, the minimum sample size needed was 63 per group or 126 in total. Final diagnosis of MBD definition In diagnosing cases of MBD, we used radiological examinations to identify bone lesions where the primary tumor was unknown and there was no previous history of malignancy at presentation. The primary malignancy of MBD was confirmed using the histopathological examination. Data collection Patients diagnosed with MBD of unknown origin based on clinical and radiological examinations will be consecutively collected. Those meeting the inclusion and exclusion criteria will be included in the sample. Data will be collected using a standardized case report form (Supplementary Material) for each sample and both intervention and control groups. Patients with incomplete medical records will be excluded. IRB approval This study has been approved by the Medical and Health Research Ethics Committee (MHREC) of the Faculty of Medicine, Public Health, and Nursing at Universitas Gadjah Mada – Dr. Sardjito General Hospital, with reference number KE/FK/0162/EC/2024. Dissemination plan Upon completion of this study, the findings will be published in a Scopus-indexed journal with a Q2-Q1 quartile ranking. Additionally, the results will be presented at the Continuing Orthopaedic Education meeting held by the Indonesian Orthopaedic Association We have revised our latest manuscript to incorporate the comments and suggestions from the reviewers. View more View less Competing Interests The authors state no conflict of interest. reply Respond Report a concern Tjandra KC. Peer Review Report For: Analysis of the effectiveness and efficiency of the Indonesian metastatic bone disease of unknown origin algorithm (INA-MBD): time to diagnosis and cost to diagnosis : Quasi-experimental study [version 2; peer review: 3 approved] . F1000Research 2024, 13 :333 ( https://doi.org/10.5256/f1000research.160158.r273174) NOTE: it is important to ensure the information in square brackets after the title is included in this citation. 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