Patients with extensive malignancies involving the femur often require total femoral replacement when their limbs can be salvaged. Reported series are small and involve heterogeneity of tumours. We present nine patients with osteosarcomas of the femur treated at our institution between 2003 and 2010 with a mean follow-up of 27 (6 to 56) months. Their ages ranged from 9 to 17 (mean 14 years). They had large volume tumours (mean 911 cm3 ) and presented late with a mean of 5.5 months from the onset of symptoms to definitive treatment. All patients underwent resection and total femur replacement. Six patients have died and two are alive with good function at the time of this report. One was lost to follow-up. These patients require a high level of treatment care and have a guarded prognosis
Osteosarcoma

OBJECTIVES: Meta-analysis is a statistical appraisal of the data analytic implications of published articles (Y), estimating parameters including the odds ratio and relative risk. This information is helpful for evaluating the significance of the findings. The Higgins I2 index is often used to measure heterogeneity among studies. The objectives of this article are to amend the Higgins I2 index score in a novel and innovative way and to make it more useful in practice. METHODS: Heterogeneity among study populations can be affected by many sources, including the sample size and study design. They influence the Cochran Q score and, thus, the Higgins I2 score. In this regard, the I2 score is not an absolute indicator of heterogeneity. Q changes by bound as Y increases unboundedly. An innovative methodology is devised to show the conditional and unconditional probability structures. RESULTS: Various properties are derived, including showing that a zero correlation between Q and Y does not necessarily mean that they are independent. A new alternative statistic, S2, is derived and applied to mild cognitive impairment and coronavirus disease 2019 vaccination for meta-analysis. CONCLUSIONS A hidden shortcoming of the Higgins I2 index is overcome in this article by amending the Higgins I2 score. The usefulness of the proposed methodology is illustrated using 2 examples. The findings have potential health policy implications.