Where Are We Now?
Because so many patients with cancer now are living longer as a result of targeted systemic therapies , skeletal metastases  and the pathological fractures they cause—especially to the hip—should force us to focus on how to improve the care of patients with this problem.
In the current study, Varady and colleagues  do exactly this; they found that taking the time to medically prepare such complex patients for surgery does not compromise their postoperative outcomes in terms of surgical complications and peri-operative mortality. This may be different than what we (think we) know about patients with osteoporotic hip fractures; studies suggest that delayed surgery in those patients is associated with a greater risk of complications and death , but whether that delay causes the excess complications remains controversial.
However, what is most striking is that Varady and colleagues  have shown that the presence of disseminated disease is associated with increased morbidity and mortality. In other words, patients with disseminated disease are high-risk surgical fixation patients and prophylactic fixation is likely to be safer for them. Although one can say this is intuitive, it does bring to light the imperative of identifying patients at risk for fracture, as surgery is safer for those undergoing prophylactic fixation compared to undergoing fixation after a fracture has occurred . Based on this, healthcare systems can introduce policies that prioritize patients with cancer and disseminated disease into screening programs to identify fractures before they occur.
Where Do We Need To Go?
In order to decrease the morbidity and mortality of pathologic fracture fixation in patients with disseminated cancer, we need to identify any lesions that will go on to fracture, and then offer prophylactic fixation. Although this is a simple statement, the reality is extremely complex. Many factors contribute to the risk for fracture, including cancer type, lesion size, lesion location, overall bone strength of the patient, and potential response to radiotherapy.
The potential risk factors for pathologic fracture of the proximal femur have been well-chronicled. These include the very basic Mirel’s criteria that consider anatomic location of the lesion, size, symptoms and radiographic density . More-advanced imaging and weight-bearing algorithms have been evaluated, including focused CT imaging of the affected bone [3, 8]. The expected survival of the patient is also an important factor in considering prophylactic fixation. Patients with an extremely short life expectancy may not be appropriate candidates for prophylactic fixation. The most widely used program available for predicting survival in this patient population is Pathfx.org [5, 12, 13]. With these available resources, we should be able to identify those patients who will benefit most from prophylactic surgery, and therefore minimize the morbidity and mortality of the surgical management of pathologic fractures once they have occurred.
Closer communication with medical oncologists is needed to reach the perfect scenario, in which all patients with disseminated cancer but with a reasonable life expectancy and with an impending pathologic fracture of the proximal femur are identified before the fracture occurs. In the future, machine learning tools can be used to prioritize patients based on their expected survival and risk for fracture. In fact, in orthopaedic oncology, machine learning tools have already been developed to predict survival in chondrosarcoma patients [2, 16].
How Do We Get There?
Patients with disseminated cancer should all be candidates for skeletal screening programs at referral cancer centers. Skeletal screening referral programs could be multidisciplinary clinics with medical oncologists, radiation oncologists, orthopaedic surgeons, and specialists in palliative care . All patients with disseminated cancer could undergo skeletal screening with either skeletal surveys or bone scans. Any lesions concerning for pathologic fracture could be evaluated clinically for local management, radiation therapy, and/or prophylactic fixation. Patients who do not undergo local management would be scheduled for regular follow-up and surveillance. This practical approach in a vulnerable patient population would avoid much of the morbidity and postoperative mortality reported by Varady and colleagues .
Although fast-track multidisciplinary cancer diagnosis and management clinics would require extra resources such as funding and support personnel, as well as systems policy mandates, these clinics have been very successful in streamlining patient triage, diagnosis, and management, and saving workload and physician time for many different types of cancers such as colorectal, breast, prostate and gynecological cancers [1, 6, 17].
Within the clinical realm of metastatic bone disease, orthopaedic surgeons would be the logical point of contact for fast-track metastatic cancer skeletal screening clinics, in conjunction with their medical and radiation oncology colleagues. In fact, the leadership of the Musculoskeletal Tumor Society (MSTS) have committed to “owning” metastatic bone disease and spearheading the multidisciplinary and surgical management of these patients with the goal of minimizing the morbidity and mortality of pathologic fractures . The MSTS is dedicated to advocating for funding for research on metastatic bone disease from the National Institutes of Health. This includes the development of machine learning tools and that can predict life expectancy and fracture risk in patients with disseminated cancer. Such research would require co-ordinated data entry from many sites in order to provide sufficient data points to train the machine learning algorithms to accurately predict the expected lifetime of the patient and risk for pathologic fracture, thus directing the screening and care of patients with metastatic bone disease.
1. Basta YL, Tytgat KMAJ, Greuter HH, Klinkenbijl JHG, Fockens P, Strikwerda J. Organizing and implementing a multidisciplinary fast track oncology clinic. Int J Qual Health Care. 2017;29:966–971.
2. Bongers MER, Thio QCBS, Karhade AV, Stor ML, Raskin KA, Lozano Calderon SA, DeLaney TF, Ferrone ML, Schwab JH. Does the SORG algorithm predict 5-year survival in patients with chondrosarcoma? An external validation. Clin Orthop Relat Res. [Published online ahead of print April 27, 2019]. DOI: 10.1097/CORR.0000000000000748
3. Damron TA, Nazarian A, Entezari V, Brown C, Grant W, Calderon N, Zurakowski D, Terek RM, Anderson ME, Cheng EY, Aboulafia AJ, Gebhardt MC, Snyder BD. CT-based structural rigidity analysis is more accurate than Mirels scoring for fracture prediction in metastatic femoral lesions. Clin Orthop Relat Res. 2016;474:643–651.
4. Falzone L, Salomone S, Libra M. Evolution of cancer pharmacological treatments at the turn of the third millennium. Front Pharmacol. 2018;9:1300.
5. Forsberg JA, Wedin R, Boland PJ, Healey JH. Can we estimate short- and intermediate-term survival in patients undergoing surgery for metastatic bone disease? Clin Orthop Relat Res. 2017;475:1252-1261.
7. Hernandez RK, Wade SW, Reich A, Pirolli M, Liede A, Lyman GH. Incidence of bone metastases in patients with solid tumors: Analysis of oncology electronic medical records in the United States. BMC Cancer. 2018;18:44.
8. Howard EL, Cool P, Cribb GL. Prediction of pathological fracture in patients with metastatic disease of the lower limb. Sci Rep. 2019;9:14133.
9. Jawad MU, Scully SP. In Brief: Classifications in brief: Mirels’ classification: Metastatic disease in long bones and impending pathologic fracture. Clin Orthop Relat Res. 2010;468:2825–2827.
10. Kimura T. Multidisciplinary approach for bone metastasis: A review. Cancers (Basel).
11. Klestil T, Röder C, Stotter C, Winkler B, Nehrer S, Lutz M, Klerings I, Wagner G, Gartlehner G, Nussbaumer-Streit B. Impact of timing of surgery in elderly hip fracture patients: A systematic review and meta-analysis. Sci Rep. 2018;8:1–15.
12. Ogura K, Gokita T, Shinoda Y, Kawano H, Takagi T, Ae K, Kawai A, Wedin R, Forsberg JA. Can a multivariate model for survival estimation in skeletal metastases (pathfx) be externally validated using Japanese patients? Clin Orthop Relat Res. 2017;475:2263-2270.
13. PathFX. About. Available at: https://www.pathfx.org/about/
. Accessed October 21, 2019.
14. Randall RL. A Promise to our patients with metastatic bone disease. Ann Surg Oncol. 2014;21:4049–4050.
15. Ristevski B, Jenkinson RJ, Stephen DJG, Finkelstein J, Schemitsch EH, McKee MD, Kreder HJ. Mortality and complications following stabilization of femoral metastatic lesions: A population-based study of regional variation and outcome. Can J Surg. 2009;52:302–308.
16. Thio QCBS, Karhade AV, Ogink PT, Raskin KA, De Amorim Bernstein K, Lozano Calderon SA, Schwab JH. Can machine-learning techniques be used for 5-year survival prediction of patients with chondrosarcoma? Clin Orthop Relat Res. 2018;476:2040-2048.
17. van Harten WH, Goedbloed N, Boekhout AH, Heintzbergen S. Implementing large scale fast track diagnostics in a comprehensive cancer center, pre- and post-measurement data. BMC Health Serv Res. 2018;18:85.
18. Varady NH, Ameen BT, Chen AF. Is delayed time to surgery associated with increased short-term complications in patients with pathologic hip fractures? Clin Orthop Relat Res. [Published online ahead of print]. DOI: 10.1097/CORR.0000000000001038